US8196835B2 - Method and apparatus for determining position and rotational orientation of an object - Google Patents

Method and apparatus for determining position and rotational orientation of an object Download PDF

Info

Publication number
US8196835B2
US8196835B2 US12/960,728 US96072810A US8196835B2 US 8196835 B2 US8196835 B2 US 8196835B2 US 96072810 A US96072810 A US 96072810A US 8196835 B2 US8196835 B2 US 8196835B2
Authority
US
United States
Prior art keywords
marker
coordinate
image
markers
position marker
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
US12/960,728
Other versions
US20110121068A1 (en
Inventor
David C. Emanuel
Larry G. Mahan
Richard H. Ungerbuehler
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Invention Discovery Co Ltd
TotalTrax Inc
Original Assignee
Sky Trax Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Sky Trax Inc filed Critical Sky Trax Inc
Priority to US12/960,728 priority Critical patent/US8196835B2/en
Assigned to SKY-TRAX, INC. reassignment SKY-TRAX, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: EMANUEL, DAVID C., MAHAN, LARRY G., UNGERBUEHLER, RICHARD H.
Publication of US20110121068A1 publication Critical patent/US20110121068A1/en
Application granted granted Critical
Publication of US8196835B2 publication Critical patent/US8196835B2/en
Assigned to SKY-TRAX, LLC reassignment SKY-TRAX, LLC MERGER AND CHANGE OF NAME (SEE DOCUMENT FOR DETAILS). Assignors: RTAC MERGER SUB, LLC, SKY-TRAX INCORPORATED
Assigned to TOTALTRAX, INC. reassignment TOTALTRAX, INC. MERGER (SEE DOCUMENT FOR DETAILS). Assignors: SKY-TRAX, LLC
Assigned to ENHANCED CREDIT SUPPORTED LOAN FUND, LP reassignment ENHANCED CREDIT SUPPORTED LOAN FUND, LP SECURITY INTEREST Assignors: TOTALTRAX, INC
Assigned to PINNACLE BANK reassignment PINNACLE BANK SECURITY INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: TOTALTRAX, INC.
Assigned to TOTALTRAX INC. reassignment TOTALTRAX INC. RELEASE BY SECURED PARTY (SEE DOCUMENT FOR DETAILS). Assignors: PINNACLE BANK
Assigned to TOTALTRAX INC. reassignment TOTALTRAX INC. RELEASE BY SECURED PARTY (SEE DOCUMENT FOR DETAILS). Assignors: ENHANCED CREDIT SUPPORTED LOAN FUND, LP
Assigned to TOTALTRAX INC. reassignment TOTALTRAX INC. RELEASE BY SECURED PARTY (SEE DOCUMENT FOR DETAILS). Assignors: PINNACLE BANK
Assigned to SHENZHEN INVENTION DISCOVERY CO., LTD. reassignment SHENZHEN INVENTION DISCOVERY CO., LTD. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: INC., TOTALTRAX
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0234Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B66HOISTING; LIFTING; HAULING
    • B66FHOISTING, LIFTING, HAULING OR PUSHING, NOT OTHERWISE PROVIDED FOR, e.g. DEVICES WHICH APPLY A LIFTING OR PUSHING FORCE DIRECTLY TO THE SURFACE OF A LOAD
    • B66F9/00Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes
    • B66F9/06Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes movable, with their loads, on wheels or the like, e.g. fork-lift trucks
    • B66F9/075Constructional features or details
    • B66F9/0755Position control; Position detectors
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B66HOISTING; LIFTING; HAULING
    • B66FHOISTING, LIFTING, HAULING OR PUSHING, NOT OTHERWISE PROVIDED FOR, e.g. DEVICES WHICH APPLY A LIFTING OR PUSHING FORCE DIRECTLY TO THE SURFACE OF A LOAD
    • B66F9/00Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes
    • B66F9/06Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes movable, with their loads, on wheels or the like, e.g. fork-lift trucks
    • B66F9/075Constructional features or details
    • B66F9/20Means for actuating or controlling masts, platforms, or forks
    • B66F9/24Electrical devices or systems
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/16Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using electromagnetic waves other than radio waves

Definitions

  • the invention presents a method, apparatus, and system for determining position and rotational orientation of an object in a predefined two-dimensional space.
  • a method, apparatus, and system to determine the position and rotational orientation of an object in a predefined space in which a machine vision image acquisition apparatus acquires an image and processes the acquired image, and a computer calculates the object's position and rotational orientation based on processed image data.
  • Position is determined in one or two dimensions.
  • Rotational orientation (heading) is determined in the degree of freedom parallel to the plane of motion.
  • the method and apparatus of the present invention present a general solution to the problem of object location and may be applied to many fields of use. Two application examples follow.
  • Radio-based navigation systems such as GPS can be used quite effectively aboard vehicles outdoors, but there exists today no ubiquitous position determination means for indoor use comparable to GPS.
  • a number of methods are used to guide robots and automatic guided vehicles (AGV) indoors, but these vehicles are often designed to move along predetermined paths.
  • AGV guidance systems commonly use embedded wiring, fixtures, or other fixed means to guide vehicles along prescribed paths.
  • Optical systems have been developed that utilize rotating laser beams to reflectively detect position markers placed horizontally, but the beam's field of view can easily become blocked in a factory or warehouse.
  • Camera based systems which view objects near a vehicle and interpret position and/or motion from image data are disclosed, but these deal with very challenging image analysis problems and are not suitable for exact position or heading determination.
  • the current invention allows vehicles full freedom of movement and freedom of rotation while maintaining the ability to determine position and rotational orientation at any location and at any rotational orientation within the designated area or volume.
  • Objects are frequently stored on indoor floors or in outdoor areas where storage devices such as bins, racks, and shelves are not available. Such areas are sometimes marked to designate locations so that objects can be placed and later found with a required degree of precision.
  • the present invention provides a method of determining precise position and rotational orientation (object attitude, rotation, or alignment) within a designated area or volume.
  • the current invention can be used on objects, people, or any stationary or moveable object that can provide the necessary electrical power and offer a view of a herein claimed position marker.
  • the invention can be attached to an industrial vehicle that places objects such as storage units within an indoor are such as a warehouse. By determining the position and vehicle heading accurately, the present invention can extrapolate the precise location of the on-board storage unit; for example a pallet.
  • the invention is suitable for indoor and outdoor use, and can be applied to stationary or mobile objects to provide a high degree of precision for position and rotational orientation measurements.
  • Determining the position and rotational orientation of an object within a defined space is a practical problem that has brought about many solutions, each dedicated toward solving the specific requirements of an application.
  • Many technologies have been applied to position determination in one, two, and three dimensions, including optical, ultrasonic, and radio, but most methods do not provide angular orientation information such as attitude, direction, or heading.
  • Other methods have been developed for angular measurement, but may lack positional determination.
  • GPS Global Positioning System
  • GPS operability suffers indoors from signal attenuation and reflections, so it is not a good choice for indoor applications.
  • Ultrasonic methods that operate well indoors have been designed to replicate GPS' capability, but they, too, lack orientation determination.
  • U.S. Pat. No. 5,832,139 discloses a method and apparatus for determining up to six degrees of freedom of a camera relative to a reference frame which comprises an optically modulated target with a camera and processing the camera's output video signal with a digital computer.
  • the target may have a single pattern, multiple patterns, or patterns of varying size, and multiple targets may be used.
  • the invention analyzes the parallax, or “warping” of square target patterns into non-square quadrilaterals within the field of view in order to determine six degrees of freedom of the camera. It does not present common bar code symbols as a choice for passively modulated targets, and does not use the inherent identity of bar code symbols for both automated means and non-automated position determination means.
  • U.S. Pat. No. 5,828,770 provides a system for determining the spatial position and angular orientation of an object in real-time using activatable markers.
  • Each marker is uniquely identified and marker relative geometry is known.
  • the system allows low cost sensors to be used, but requires active markers, such that upon loss of power, the markers become undetectable by the sensor
  • U.S. Pat. No. 5,367,458 discloses an apparatus and method for verifying the identity of an observed anonymous target from a plurality of anonymous targets positioned at predetermined locations within an area of operation where a guided vehicle is provided. This method offers two dimensional position and one-degree-of-freedom angular determination. Said targets are adhered to surrounding walls of the operation area, but they may become obscured in a factory or warehouse where stacks of materials may block the line of sight between detector and target.
  • U.S. Pat. No. 5,051,906 utilizes overhead retroreflective ceiling markers and an optical sensing means to determine a vehicle's position and orientation.
  • this method includes a light source and camera that are pitched up obliquely at an angle between horizon and zenith.
  • the markers are strip-like retroreflective features which are aligned with the axis of a hallway. In that the feature presents a pattern or alignment which is substantially parallel to a long axis of the hallway the pattern is detected and processed to derive robot navigation information.
  • This system determines position and direction, but is aimed at directing a vehicle along a hallway, and not freely within a large area. It does not utilize self-identifying machine readable position markers.
  • U.S. Pat. No. 6,556,722 A more sophisticated use of ceiling markers is disclosed in U.S. Pat. No. 6,556,722, wherein circular barcodes are utilized to indicate reference positions within a television studio.
  • a television studio camera is equipped with a secondary camera which views position markers set onto the studio ceiling in known locations.
  • the markers are constructed of concentric ring barcodes which are developed specifically for the purpose.
  • Camera position is determined by capturing an image of at least three markers and performing geometric analysis in a digital computer to determine accurate location within the three-dimensional studio space. Zoom and focus servos control the secondary camera's view and assist in marker locating.
  • the invention discloses proprietary circular ring barcodes, which cannot be read by commercial machine vision systems, and requires a multiplicity of markers to be within view.
  • U.S. Pat. No. 6,859,729 discloses a combination of GPS, laser, compass, and wheel encoders to form a vehicle navigation system. Upon dropout of the GPS, the vehicle is navigated using a laser tracking system and one or both of the compass and wheel encoder detection means.
  • the navigation system may be used to remotely control mine detection vehicles, where outdoor and indoor environments may be encountered.
  • the system recalibrates optically with waypoint markers, and includes inertial navigation. Complexity and cost are drawbacks to implementing this method.
  • U.S. Pat. No. 6,732,045 detects the magnitude and angle of incremental motion vectors relating to the movement of a vehicle within a predetermined space.
  • a plurality of sensors is used, including a laser beam with corresponding optical position markers placed at known positions and encoders which detect and encode wheel rotation and axle angular position. Vehicle position and angular orientation are determined through vector addition.
  • Shortcomings of this invention include the assumption that wheel diameter is unchanging, that no wheel slip occurs, and that the resolution of wheel encoders is sufficient for the application.
  • the invention requires multiple sensors, and does not provide an alternative means of determining approximate location in the event of primary system failure.
  • U.S. Pat. No. 6,728,582 provides a system and method for estimating the position of an object in three dimensions using two machine vision cameras interconnected with a machine vision search tool. A nominal position for each camera's acquired image of the object is determined and a set of uncertainty vectors along each of the degrees of freedom is generated. This method requires viewing multiple objects with multiple cameras in order to make the weighted estimation.
  • Rotational orientation determination is not present in many position determination methods, and becomes important in applications such as vehicle tracking and vehicle guidance in order for a guidance system to properly direct the vehicle.
  • goods may be stored in chosen orientations, for example with carton labels aligned in a particular direction or pallet openings aligned to facilitate lift truck access from a known direction.
  • the combination of position determination and angular orientation determination using a single sensor is therefore desired.
  • An improved method and apparatus must reduce or remove the shortcomings of current methods, provide general applicability, and offer high accuracy.
  • the present invention provides a method and an apparatus for accurately determining position and rotational orientation within a predefined space, such as a designated area or volume inside a building.
  • the present invention can be employed to determine location in one or two dimensions and rotational orientation in one degree of freedom. It can be applied to stationary and/or mobile objects and can measure the objects position and orientation in real-time as it moves freely within the designated area.
  • the present invention which is based on a single optical sensor, overcomes line of sight obscuration problems by providing position markers placed opposite the plane of the object's motion.
  • the plane of the object's location is typically a floor, and position references are placed overhead.
  • the present invention provides a reliable and accurate method and apparatus that can be used in many situations. It is suitable for stationary or mobile objects, slow or fast motion, incremental or continuous measurement, indoor or outdoor use, and can serve as the sensory apparatus and method for a guidance system, navigation system, or position monitoring system. While the specific purpose is to track industrial vehicles indoors, it can be applied to track objects of almost any sort, including railcars, heavy equipment, storage containers, people, animals, and so on. It can also be applied to map the location of marked objects in designated areas such as archeological sites, excavations, outdoor storage areas, and mines.
  • the method of the present invention determines a coordinate position and rotational orientation (i.e., directional heading) of an object within a predefined coordinate space.
  • the method comprises the steps of:
  • the step of calculating the position of the object and the rotational orientation of the object in the coordinate space further comprises:
  • Position and rotational orientation are determined by acquiring images of position markers which are placed at known locations in or near the coordinate space, i.e., the region of interest. Subsequent image analysis is performed by commercially available machine vision equipment consisting of one or more cameras and image processing system(s). The position and rotational orientation of one or more position markers relative to a camera's view are determined by the machine vision equipment; the position and rotational orientation in “real” space are then computed from machine vision data using a series of programmed instructions which translate the relative positional and rotational orientation data to coordinates expressed in usable units such as feet or meters. Results are stored, displayed, and/or transmitted to another system, such as a post processing system, where data may be used to record object location, to direct vehicle guidance, or for other navigation or control purposes.
  • a post processing system such as a post processing system, where data may be used to record object location, to direct vehicle guidance, or for other navigation or control purposes.
  • Embodiments of the present invention are also directed to an apparatus useful for determining a coordinate position and rotational orientation of an object within a predefined coordinate space.
  • the apparatus comprising:
  • the image acquisition system comprises a machine vision system, the machine vision system comprising a camera, a light source, and image capture electronics wherein the light source of the machine vision system is located adjacent to the camera.
  • FIG. 1 shows the overall system in one embodiment in accordance with the present invention and identifies key elements coordinate reference 1 , position markers 2 , machine vision camera 4 , data processing device 5 , vehicles 6 , handheld bar code scanner 7 , wireless data communications links 8 , and illumination source 9 .
  • FIG. 2 illustrates two implementations of coordinate reference 1 , showing arrays of two types of position markers: type 2 (employing linear bar code symbols) on the left drawing half, and position markers type 3 (employing two-dimensional bar code symbols) on the right drawing half.
  • FIG. 3 illustrates details of position marker 2 , showing substrate 2 a , label 2 b , and imprinted upon the label geometric position references 12 , linear bar code symbol 11 , and human readable marker identification 10 .
  • FIG. 4 defines key points A and B, point C (the midpoint of line AB which defines the center of the symbol), and dimension D of position marker 2 .
  • FIG. 5 shows position marker 2 rotated counterclockwise with respect to Cartesian coordinate axes X and Y and defines angle BCE as the angle of rotation.
  • FIG. 6 shows a camera's field of view with one entire position marker and one partial position marker in view.
  • the distance between the center of the field of view (point O) and the center of the position marker (point C) is defined as line segment OC.
  • Angle XOC is defined as the radial angle from the X axis to the position marker.
  • FIG. 7 shows a sample Look-Up-Table containing position marker data.
  • FIG. 8 presents a high level software flow diagram for the general solution using marker type 2 .
  • FIG. 9 presents a software flow diagram for image processing and feature extraction steps.
  • FIG. 10 shows a software flow diagram for expected position and rotational orientation determination.
  • FIG. 11 shows a software flow diagram for the calculation of actual position and rotational orientation.
  • FIG. 12 shows position marker type 3 with a two-dimensional bar code symbol 13 , substrate 3 a , label 3 b , and human readable text 10 .
  • FIG. 13 defines key points J, K, and L of position marker 3 .
  • FIG. 14 defines point N (the midpoint of line JK), which defines the center of the symbol, and dimension M of position marker 3 .
  • Angle JLP indicates the rotational angle with respect to Cartesian coordinate axes X and Y.
  • FIG. 15 shows a camera's field of view with one entire position marker and one partial position marker in view.
  • the distance between the center of the field of view (point O) and the center of the position marker (point N) is defined as line segment ON.
  • Angle XON is defined as the radial angle from the X axis to the position marker.
  • FIG. 16 shows a sample Look-Up-Table containing position marker data.
  • FIG. 17 presents a software flow diagram for image processing and feature extraction steps for marker type 3 .
  • FIG. 18 shows a software flow diagram for expected position and rotational orientation determination.
  • FIG. 19 shows a software flow diagram for the calculation of actual position and rotational orientation.
  • FIG. 20 shows an alternate embodiment whereby the machine vision camera is placed overhead and position markers are applied to the vehicle.
  • FIG. 21 shows an arrangement of multiple overhead cameras tracking multiple vehicles.
  • FIG. 22 shows a software flow diagram for the embodiments illustrated in FIGS. 20 and 21 .
  • the present invention provides a novel method of determining position and rotational orientation through the following steps:
  • the determination of position and rotational orientation in a designated area is accomplished by contemporary machine vision equipment using a coordinate reference, comprising a plurality of unique position markers, which is placed within or near to the designated area or volume. Sufficient position markers are provided so that at least one position marker of the coordinate reference is visible to the determination system from each and every location within the designated area or volume.
  • Machine readable symbols such as one-dimensional or two-dimensional barcodes, encode the identity of each position marker of the coordinate reference, allowing bar code scanning devices 7 ( FIG. 1 ) to read the identities of the symbols in addition to, or in lieu of the current invention's automated system.
  • Position data in human readable form may also be imprinted, attached, or otherwise affixed to the position markers if desired. Printed text allows determination of approximate location by simply viewing the coordinate reference and reading the text on the nearest position marker.
  • Machine recognizable symbols are arranged on the position markers of the coordinate reference at predetermined positions, allowing machine vision technology to determine position by analyzing the shapes and symbols on the position markers. Exact position coordinates and rotational orientation are determined through computer programmed instructions which are based upon geometric analysis of acquired image data.
  • two-dimensional non-symmetric, non-concentric barcode symbols are utilized to serve the dual purpose of machine readable position location codes and geometric position markers.
  • Coordinate reference 1 is not required for the invention, but may provide physical support for position markers if no other structures such as ceilings, beams, walls, etc. are available for direct attachment of the markers.
  • the coordinate reference may be constructed of any of several air-permeable or perforated materials (example: netting) or solid materials (example: plastic sheet). Netting examples include fish net, basketball net, fence net, screen (window screen, tent screen), and mesh (examples: garment lining, landscaping mesh).
  • Solid materials include sheet or webs such as polyolefin film, non-woven synthetic material, and paper. Perforated or permeable materials offer the advantage of allowing air to pass through, for example, to accommodate indoor ventilation.
  • Perforated, transparent, and translucent materials offer the advantage of allowing light to pass through the coordinate reference, for example to allow room lighting to be transmitted.
  • Solid materials which may also be perforated (example: paper with punched holes), may be used and may be opaque, translucent, or transparent, depending on lighting and ventilation requirements for the application. Either solid or perforated materials can be readily used to implement the invention.
  • the coordinate reference is sized to match the predefined space, volume, or area to be controlled.
  • the purpose of the coordinate reference 1 is to simply provide a convenient surface on which a plurality of unique position markers 2 , 3 can be imprinted, attached or affixed. Lacking a coordinate reference, position markers may be applied directly to a ceiling, roof, wall, beam, or other structure, or may be suspended, supported, or attached to nearby structure.
  • the coordinate reference may be supported by building structure, for example, by factory or warehouse ceiling beams if the coordinate reference is to be suspended overhead. Free standing fixtures or other fixed structure may be used for other orientations; for example, the coordinate reference may be attached to a wall parallel and opposite to a wall on which objects are desired to be tracked. In some cases, position markers may be attached directly to building structures without the necessity of affixing them first to a secondary surface.
  • Position markers 2 and 3 are constructed from any material on which printing can be done directly or can be applied, as a label. Mechanical sturdiness is an important factor for assuring marker longevity, and many materials offer adequate printability and sturdiness. Paper, sheet goods, plastic sheeting, cardboard, metal, and other common materials are suitable.
  • the markings can be dark on a light or transparent background, light on a dark or opaque background, or of one or more colors. Marker attachment to the coordinate reference may be by fasteners such as screws, clips, or wire ties, adhesives such as glue or pressure sensitive label adhesive.
  • the position markers can be imprinted directly on the coordinate reference using silkscreen, lithographic, or offset printing methods.
  • the coordinate reference may be substantially planar or non-planar. It is necessary only that each marker has a unique identity and that the position, orientation, and size of each marker relative to the designated area is known.
  • Position markers are imprinted upon or attached to the coordinate reference 1 in a prescribed pattern; for example, in rows and columns corresponding to a desired coordinate plan for the designated area.
  • position markers may be read by humans, or to be scanned by bar code scanners. These alternative methods offer assurance that position information can be determined even though the automated method of the present invention is inoperative, for example, during a power failure. Linear bar codes 11 in position marker 2 are selected for these implementations.
  • the position marker 3 of FIGS. 12 and 13 provides information equivalent to that of position marker 2 , but does so with a single graphic; in this case, a two-dimensional bar code symbol.
  • the marker is comprised of text 10 , and barcode 13 , which serves the dual purpose of encoding the marker identity and, due to its non-symmetric form, serving as a position and angular orientation reference.
  • Contemporary machine vision technology is utilized to capture and process images of the coordinate reference and position markers. Offering sophisticated image processing capabilities such as presence or absence detection, dimensional measurement, and object shape identification, machine vision systems are typically comprised of a video camera, a computing device, and a set of software routines. Machine vision equipment is commercially available and suitable for most environments. In order to develop a machine vision application, the user chooses certain subroutines, combines them into a sequence or procedure, and stores the procedure in the memory or storage device of the machine vision computing device.
  • the present invention includes a set of software instructions that calls certain procedures to capture images, adjust images for readability, analyze images to detect features, and measure detected features to determine geometric data such as object size or location within the camera's field of view. Output data are produced at the conclusion of each procedure and may be stored or transferred to another device.
  • the present invention provides a second computing device to (a) calculate the object's position with high precision, (b) calculate the object's rotational angle with high precision, (c) compensate for position marker installation inconsistencies, and (d) translate position and orientation values into convenient units.
  • the coordinate reference is made from thermoplastic flat net such as CintoFlex “D”, available from Tenax Corporation.
  • the material is lightweight, strong, and inexpensive.
  • the net is cut to the dimensions sufficient to cover the area of interest; for example, it can be cut to the size of a storage area. Multiple nets can be adjoined side by side to cover large areas. Alternatively, the net can be cut into strips wide enough to support rows of position markers, whereby each strip spans across a particular area within a building, and the strips are suspended in parallel with one another.
  • Position markers 2 are fabricated of two components; a label 2 b and a backing plate 2 a . Labels are printed using common bar code label printers such as the Intermec Model 3600 Thermal/Thermal Transfer printer. Label stock such as Duratran II Thermal Transfer Label Stock, part No. E06175, also available from Intermec Corporation, is available from many suppliers. Bar code symbols, each containing a unique identification encoded in 1-D bar code symbology are printed on the label stock, along with human readable text. Bar codes of most standard formats are usable; for example, Code 39, Code 128, CODABAR, UCC/EAN128, and Interleaved Two-Of-Five (ITF) codes are common.
  • ITF Interleaved Two-Of-Five
  • the labels are then adhesively affixed to a stiffer substrate, or backing plate, 2 a , to add mechanical strength.
  • a stiffer substrate or backing plate, 2 a
  • Many materials can be used for backing plates, but for its low cost and ease of use, white 0.030 inch thick PVC (polyvinyl chloride) is a good choice.
  • the backing plate is sized larger than the label to provide an optical quiet zone around each bar code symbol. Attachment of the backing plate to the coordinate reference net can be done in many ways, using staples, glue, weldments, etc., but is preferably done with plastic wire ties. Attachment is done by inserting tie into holes which have been punched or drilled in the backing plates, and threading the ties through the net.
  • FIG. 1 illustrates a typical embodiment in a warehouse, where materials are stored on the floor.
  • Coordinate reference 1 based on the net/screen/mesh design is suspended from overhead, and is placed sufficiently high above the working area so as not to interfere with operations. Suspension is provided by mechanical supports such as cables, wire, or building structure (not shown), or the reference is attached directly to the ceiling, whereupon the material assumes a substantially planar form.
  • the semi-open structure allows much light to pass from overhead light fixtures to the work area, and air to flow freely for heating and ventilation considerations.
  • Position markers 2 on coordinate reference 1 identify coordinate locations. After being installed in the warehouse facility, the markers remain stationary. Each marker therefore corresponds to a particular location on the warehouse floor, and a database of these locations is created and stored in a computational device (digital computer) 5 .
  • the data base may be generated in advance of coordinate reference installation, and populated with expected values. It may be modified after installation if a physical survey determines that discrepancies exist between expected values and actual values for marker locations, rotation angles, or dimensions. Markers commonly share uniform dimensions, but some applications may require markers of different sizes. Image analysis routines are presented to correct for varied marker size or varied distance from the camera to the markers.
  • Vehicles 6 have affixed to them machine vision cameras 4 .
  • Illumination source 9 may be required for dark operations such as in dimly illuminated warehouses.
  • the light source may be a spotlight, floodlight, strobe, LED, or other conventional source.
  • the preferred embodiment utilizes room lighting.
  • Computer 5 can reside on-board as shown on the fork lift truck of FIG. 1 , or be out boarded as shown on the van.
  • Standard commercial wireless data communication network equipment 8 provides data transmission between vehicles not equipped with on-board computers and a computer 5 stationed remotely.
  • the vehicles have freedom of motion in two dimensions within the operating area; therefore, the invention embraces two-dimensional analysis, plus single degree-of-freedom rotation (heading) determination.
  • the position and rotational orientation determination system is active at all times when the vehicle is within the designated area beneath position reference 1 .
  • Camera images may be captured continuously, or on command, such as when the vehicle stops, or at a time chosen by the operator.
  • the camera 4 captures an image of the overhead position reference 1 the image is transmitted to the machine vision system computational device 5 for analysis.
  • the method of the preferred embodiment utilizes callable vendor-supplied subroutines to analyze position markers and store data obtained from the analysis. Rotational orientation and position are calculated from these data and stored or transferred to other devices.
  • the preferred embodiment applies a commercial machine vision system such as Model 5100 or Model 5400 from Cognex, Incorporated.
  • Model 5100 or Model 5400 from Cognex, Incorporated.
  • “In-Sight ExplorerTM” software provided with this system offers a wide array of feature extraction, mathematical, geometric, object identification, and barcode symbol decoding subroutines.
  • the following functional steps analyze the image within the field of view, identify position markers, decode the position markers' encoded position information, calculate X-Y coordinates in pixel space, and convert the results to actual position and heading.
  • FIG. 8 presents a condensed flow diagram. The process produces four separate sets of data: marker ID 300 , approximate position 400 , expected position and heading 500 and actual position and heading 600 .
  • an image is captured 110 by the machine vision camera and stored into its memory. Analysis begins by locating 120 a readable position marker image (image in which the bar code can be decoded) within the field of view. In normal circumstances and by design, at least one position marker will be present within the field of view. Once a marker has been located, the marker identification is decoded 130 and the data is stored in the machine vision system memory 4 and is available as an output 300 . Marker positions are stored in a look-up table ( FIG. 7 ) in computer 5 , and the table can be accessed to return the approximate camera position 400 . In other words, by knowing that the camera is viewing a particular marker we can place the camera within the approximate region of that marker.
  • Markers may be directly encoded with position information, or they may be serially encoded with non-meaningful “license plate” numbers.
  • Direct encoding allows the decoded ID to translate directly into real coordinates; for example, marker 100250 may be encoded to mean “100 feet south, 250 feet west”.
  • Approximate position 400 is calculated in this manner, based on decoded marker ID and a transformation scalar to convert pixels into feet.
  • Serial encoding may be chosen whereby the ID has no inherent meaning and a look-up table contains references to the actual position.
  • the image is next analyzed 150 to determine the relative location, orientation, and size of the marker within the field of view.
  • the marker's angular orientation and its azimuth from the center of the field of view are calculated and stored in degrees.
  • Expected position and orientation can then be calculated 160 using plane geometry for markers that directly encode position. This step cannot be done for serialized markers unless the look-up table of FIG. 7 is accessed.
  • Expected position and heading 500 assume the marker's position and orientation are exactly where the encoded value places it. Actual values may differ if the marker is installed slightly offset its intended location or orientation.
  • Marker ID, relative position within the field of view, angular orientation, and marker dimensions are passed to a second processor 5 .
  • the decoded ID serves as a key to access true marker position data 170 , which is obtained from a lookup table in the second computer.
  • the marker's actual position is then calculated 180 from the marker's position within the field of view; that is, how far from the center of the field of view, and at what azimuth, as in step 160 , but using actual positional and orientation values.
  • the results are transformed from pixels into real dimensions such as feet or meters.
  • the results 600 can be saved and/or conveyed to other devices for storage, presentation, or other purpose.
  • the cycle repeats 200 once a full determination has been made.
  • Image Capture and Marker Identification 100 , 110 , 120 , 130 , and 300 .
  • the machine vision camera 4 continuously, or on command, captures analog and/or digital images of the position markers 2 of the coordinate reference 1 .
  • One or more position markers 2 are partially or fully visible within the camera's field of view at any given time.
  • the software analyzes it as follows:
  • Image data 20 is manipulated by preprocessing routines 21 to enhance image features such as sharpness, contrast, and brightness.
  • the resulting processed image is tested 22 for image brightness and contrast.
  • the image is returned for additional processing 23 if not adequate for interpretation.
  • decoder 27 If a single marker is found, selected image data are passed to a decoder 27 ; if multiple markers are present, image data are passed to a readability test 26 , which determines which marker is most readable and passes the selected image data to the decoder 27 . Alternatively, the readability test may select the marker closest to the center of the image and pass that image data to the decoder 27 . Decoder 27 “reads” the encoded unique identification code of the position marker and returns alphanumeric data which are stored as decoded position marker identification data 300 . An example of an encoded one-dimensional bar coded position marker is shown in FIG. 4 . Selected image data for a single marker are also passed to position marker key point locator 29 which analyzes image data to locate key points A, B, and C of the position marker symbol ( FIG. 7 ). Key points are then stored 30 as pixel coordinates.
  • the locating mechanism 24 first finds bar codes within the field of view; then steps 25 through 27 proceed to decode the barcode. “Blobs” (contiguous dark areas on light backgrounds) nearest to the chosen bar code are located, and the centers of the blobs are determined. Since one blob is always larger than the other for any given marker, the areas of the two are calculated and compared.
  • the key points for the position marker are defined to be the centers of the circular position references 12 .
  • Marker identification can be translated directly into real X and Y position data for markers that are directly encoded.
  • marker ID 100250 might translate directly as “100 feet south and 250 feet west”. Having this marker within the field of view implies that the camera (object) is somewhere near this point, but not necessarily exactly at this point. With markers spaced ten feet apart, the camera and object would probably lie within half-marker spacing, or five feet. Object orientation is not determined.
  • a geometric analysis of the marker's position and rotation relative to the field of view can more accurately determine the camera's position and orientation.
  • Pixel coordinates of Key Points B and C, 30 are used to calculate angle BCE, 34 , the rotation angle of the position marker relative to the field of view.
  • Angle BCE is illustrated in FIG. 5 and shown in the camera's field of view in FIG. 6 .
  • X and Y values of pixel coordinates A and C, 30 are summed and divided by two ( 37 ) to establish Point E ( FIG. 10 ), the midpoint of line segment AC, and the center of the position marker.
  • Point E coordinates are used to calculate: (a) angle XOC, FIG. 11 , the radial angle between the center of the image and the center of the position marker; and (b) the length of line segment OC, which is equal to the radial distance from the center of the image (center of the camera), Point O, to the center of the position marker, Point E.
  • the Position Marker Look-Up Table 31 ( FIG. 7 ) is a database containing actual X, Y, and Z coordinates and rotational orientations that have been measured and recorded for all position markers at the time of the coordinate reference installation. Coordinate values are recorded in conventional units, such as feet, meters and degrees.
  • the coordinate reference (leftside of drawing) includes markers AA01, AA02, etc.
  • X values correspond in the example to the north/south coordinate; Y values to east/west coordinate; Z values to marker height above the floor, ⁇ values correspond to the difference between the marker's rotational angle and its nominal angle, and the size value records the marker's dimensions referenced to the length of line segment AB.
  • Actual orientation is calculated 44 as the sum of the expected orientation and the look-up table value of ⁇ .
  • Actual position is recalculated 46 exactly as in steps 150 and 160 , but using look-up table data instead of expected (assumed) X and Y data.
  • Apparent marker size 43 is applied as an adjustment factor in calculation 46 for markers whose dimensions differ from nominal.
  • Decoded marker ID 300 is used in FIG. 11 to search look-up table 31 .
  • the results of this calculation are stored in memory.
  • Key Points A and B are used to calculate the length of Line Segment AB of the image. Since the distance AB on the position marker 3 is known and the focal length of the lens of the camera 4 is known, the distance from the camera 4 to the position marker can be determined from the ratio of the length of Line Segment AB in the image to the distance AB on the position marker 3 . With the Z coordinate of the position marker 3 also known, the Z coordinate of the object may be readily calculated.
  • the Z coordinates are stored in memory.
  • the final step is the calculation and combination 46 of actual rotational orientation and X and Y coordinates into a single unit of data which can be stored in local memory or transmitted to other devices.
  • Rotational orientation and position data derived from the image processing steps may be optionally transformed into alternate units to indicate specific regions such as a zones, sectors, or areas.
  • Coordinate reference 1 consists of position markers 3 ( FIG. 12 ), which are fabricated of labels 3 b and substrates 3 a .
  • Bar code symbols each containing a unique identification encoded in two-dimensional bar code symbology are printed on the label stock, along with human readable text.
  • Bar codes of standard formats can be used including DataMatrix, Code One, PDF417, Array Tag, and QR Code. DataMatrix symbols are chosen in this embodiment for their ubiquitous usage, error correction robustness, and well developed suite of image processing software available in commercial machine vision systems.
  • Image Capture and Marker Identification 100 , 110 , 120 , 130 , and 300 .
  • the machine vision camera 4 continuously, or on command, captures analog and/or digital images 20 of position markers 3 . At least one marker is fully visible within the camera's field of view at any given time.
  • the software analyzes it as in the preferred embodiment for steps 21 through 27 .
  • the chosen marker is analyzed to locate key points J, K, and L, which are defined in FIG. 13 . Key point coordinates are stored 30 for each point, and marker ID is decoded and available as an output 300 .
  • marker identification can be translated directly into real X and Y position data for markers that are directly encoded. Object orientation is not determined.
  • Geometric analysis of the marker's position and rotation relative to the field of view can more accurately determine the camera's position and orientation as in the earlier example.
  • Pixel coordinates of Key Points J and L, 30 are used to calculate angle JLP, 34 , the rotation angle of the position marker relative to the field of view.
  • Angle JLP is illustrated in FIG. 14 and shown in the camera's field of view in FIG. 15 .
  • X and Y values of pixel coordinates J and K, 30 are summed and divided by two ( 37 ) to establish Point N ( FIG. 14 ), the midpoint of line segment JK, and the center of the position marker.
  • Point N coordinates are used to calculate (a) angle XON ( FIG.
  • Position Marker Look-Up Table 31 ( FIG. 16 ) is the same as described earlier. Actual orientation is calculated 44 as the sum of the expected orientation and the look-up table correction value. Actual position is recalculated 46 exactly as in steps 150 and 160 , but using look-up table data instead of expected (as decoded) X and Y data. Apparent marker size 43 is applied as an adjustment factor in calculation 46 for markers whose dimensions differ from nominal.
  • the final step is the combination 46 of actual rotational orientation and X and Y coordinates into a single unit of data which can be stored in local memory or transmitted to other devices.
  • Rotational orientation and position data derived from the image processing steps may be optionally transformed into alternate units to indicate specific regions such as a zones, sectors, or areas.
  • FIG. 20 presents an application example, where machine vision camera 4 is mounted overhead and a position marker 2 or 3 is affixed to a vehicle.
  • the camera views a predetermined area as vehicle 6 moves about the area.
  • the marker is within the field of view so long as the vehicle remains within the predetermined area.
  • Image processing steps are identical to embodiment 1 and 2, with the exception that camera coordinates in real space are used as a reference point, and object coordinates are calculated from image data.
  • Image analysis steps are identical to earlier examples, but the transformation of image data into position data differs; in this arrangement the system determines where a viewed object is located instead of determining where the system itself is located. Orientation is calculated directly as before.
  • FIG. 21 An illustration of the second arrangement is presented in FIG. 21 , wherein a plurality of machine vision cameras tracks vehicles. Three predetermined coverage zones are shown, each covered by a separate machine vision camera. The drawing illustrates zones of no coverage, where a vehicle is not detected by the system, and zones of overlapping coverage, where multiple cameras detect and cross-check vehicle location and orientation.
  • Computer 5 is connected to cameras via standard wired or wireless networks and performs the same functions described above for each camera, but in addition, records the location of all vehicles within the three areas.
  • the location and orientation of all markers (e.g. vehicles) in the plurality of fields of view can be stored, graphically displayed, or transmitted to other systems such for purposes of fleet management, collision avoidance, and so forth.
  • the invention can keep track of the last known position of each vehicle; vehicle speed can be calculated, and predictions can be made for vehicle location in areas of no coverage and for impending collisions between vehicles.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Transportation (AREA)
  • Structural Engineering (AREA)
  • Electromagnetism (AREA)
  • Geology (AREA)
  • Mechanical Engineering (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Civil Engineering (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

A method and apparatus for determining position and rotational orientation of an object within a predetermined area is disclosed. Position markers, encoded with their identity, are viewed with a camera, images are captured and processed, and the position and rotational orientation of the object are calculated. Three embodiments are disclosed; the first having a camera mounted on the movable object while position markers bearing linear bar codes are fixed in location, the second having a camera mounted on the movable object while position markers bearing two-dimensional bar codes are fixed in location, and the third having a position marker of either type affixed to the object while the camera is fixed in location.

Description

PRIORITY CLAIM
This application is a continuation application of U.S. patent application Ser. No. 11/292,463, filed Dec. 3, 2005, which claims the benefit of U.S. Provisional Application Ser. No. 60/635,813, filed Dec. 14, 2004.
SCOPE OF THE INVENTION
The invention presents a method, apparatus, and system for determining position and rotational orientation of an object in a predefined two-dimensional space.
FIELD OF THE INVENTION
A method, apparatus, and system to determine the position and rotational orientation of an object in a predefined space, in which a machine vision image acquisition apparatus acquires an image and processes the acquired image, and a computer calculates the object's position and rotational orientation based on processed image data. Position is determined in one or two dimensions. Rotational orientation (heading) is determined in the degree of freedom parallel to the plane of motion.
The method and apparatus of the present invention present a general solution to the problem of object location and may be applied to many fields of use. Two application examples follow.
Vehicle Tracking
It would be useful to know the location and movement of vehicles such as industrial lift trucks indoors. Radio-based navigation systems such as GPS can be used quite effectively aboard vehicles outdoors, but there exists today no ubiquitous position determination means for indoor use comparable to GPS. A number of methods are used to guide robots and automatic guided vehicles (AGV) indoors, but these vehicles are often designed to move along predetermined paths. AGV guidance systems commonly use embedded wiring, fixtures, or other fixed means to guide vehicles along prescribed paths. Optical systems have been developed that utilize rotating laser beams to reflectively detect position markers placed horizontally, but the beam's field of view can easily become blocked in a factory or warehouse. Camera based systems which view objects near a vehicle and interpret position and/or motion from image data are disclosed, but these deal with very challenging image analysis problems and are not suitable for exact position or heading determination.
The current invention allows vehicles full freedom of movement and freedom of rotation while maintaining the ability to determine position and rotational orientation at any location and at any rotational orientation within the designated area or volume.
Stored Goods Location Determination
Objects are frequently stored on indoor floors or in outdoor areas where storage devices such as bins, racks, and shelves are not available. Such areas are sometimes marked to designate locations so that objects can be placed and later found with a required degree of precision.
The present invention provides a method of determining precise position and rotational orientation (object attitude, rotation, or alignment) within a designated area or volume. Just as it is applied to vehicles, the current invention can be used on objects, people, or any stationary or moveable object that can provide the necessary electrical power and offer a view of a herein claimed position marker. Alternatively, the invention can be attached to an industrial vehicle that places objects such as storage units within an indoor are such as a warehouse. By determining the position and vehicle heading accurately, the present invention can extrapolate the precise location of the on-board storage unit; for example a pallet. Further, the invention is suitable for indoor and outdoor use, and can be applied to stationary or mobile objects to provide a high degree of precision for position and rotational orientation measurements.
BACKGROUND OF THE INVENTION
Determining the position and rotational orientation of an object within a defined space is a practical problem that has brought about many solutions, each dedicated toward solving the specific requirements of an application. Many technologies have been applied to position determination in one, two, and three dimensions, including optical, ultrasonic, and radio, but most methods do not provide angular orientation information such as attitude, direction, or heading. Other methods have been developed for angular measurement, but may lack positional determination.
For example, Global Positioning System (GPS) is a widely recognized position determination technology, but it lacks orientation determination capability for stationary objects. GPS operability suffers indoors from signal attenuation and reflections, so it is not a good choice for indoor applications. Ultrasonic methods that operate well indoors have been designed to replicate GPS' capability, but they, too, lack orientation determination.
Various optical methods are known to determine position and orientation. U.S. Pat. No. 5,832,139 discloses a method and apparatus for determining up to six degrees of freedom of a camera relative to a reference frame which comprises an optically modulated target with a camera and processing the camera's output video signal with a digital computer. The target may have a single pattern, multiple patterns, or patterns of varying size, and multiple targets may be used. The invention analyzes the parallax, or “warping” of square target patterns into non-square quadrilaterals within the field of view in order to determine six degrees of freedom of the camera. It does not present common bar code symbols as a choice for passively modulated targets, and does not use the inherent identity of bar code symbols for both automated means and non-automated position determination means.
Similar to the above reference, U.S. Pat. No. 5,828,770 provides a system for determining the spatial position and angular orientation of an object in real-time using activatable markers. Each marker is uniquely identified and marker relative geometry is known. The system allows low cost sensors to be used, but requires active markers, such that upon loss of power, the markers become undetectable by the sensor
Pertaining to vehicle guidance, U.S. Pat. No. 5,367,458 discloses an apparatus and method for verifying the identity of an observed anonymous target from a plurality of anonymous targets positioned at predetermined locations within an area of operation where a guided vehicle is provided. This method offers two dimensional position and one-degree-of-freedom angular determination. Said targets are adhered to surrounding walls of the operation area, but they may become obscured in a factory or warehouse where stacks of materials may block the line of sight between detector and target.
U.S. Pat. No. 5,051,906 utilizes overhead retroreflective ceiling markers and an optical sensing means to determine a vehicle's position and orientation. Applied to mobile robots, this method includes a light source and camera that are pitched up obliquely at an angle between horizon and zenith. The markers are strip-like retroreflective features which are aligned with the axis of a hallway. In that the feature presents a pattern or alignment which is substantially parallel to a long axis of the hallway the pattern is detected and processed to derive robot navigation information. This system determines position and direction, but is aimed at directing a vehicle along a hallway, and not freely within a large area. It does not utilize self-identifying machine readable position markers.
A more sophisticated use of ceiling markers is disclosed in U.S. Pat. No. 6,556,722, wherein circular barcodes are utilized to indicate reference positions within a television studio. In this optically based method, a television studio camera is equipped with a secondary camera which views position markers set onto the studio ceiling in known locations. The markers are constructed of concentric ring barcodes which are developed specifically for the purpose. Camera position is determined by capturing an image of at least three markers and performing geometric analysis in a digital computer to determine accurate location within the three-dimensional studio space. Zoom and focus servos control the secondary camera's view and assist in marker locating. The invention discloses proprietary circular ring barcodes, which cannot be read by commercial machine vision systems, and requires a multiplicity of markers to be within view.
Three dimensional position determination is accomplished in U.S. Pat. No. 6,542,824 through the use of a portable electronic device that uses inertial sensors when GPS signals are not used. Inertial methods can provide orientation detection, but do not provide accuracy obtainable by other methods and are subject to drift through time.
In order to track vehicles indoors, a number of integrated applications have been developed wherein several technologies are used in combination to assure positional and angular measurement. For example, U.S. Pat. No. 6,859,729 discloses a combination of GPS, laser, compass, and wheel encoders to form a vehicle navigation system. Upon dropout of the GPS, the vehicle is navigated using a laser tracking system and one or both of the compass and wheel encoder detection means. The navigation system may be used to remotely control mine detection vehicles, where outdoor and indoor environments may be encountered. The system recalibrates optically with waypoint markers, and includes inertial navigation. Complexity and cost are drawbacks to implementing this method.
U.S. Pat. No. 6,732,045 detects the magnitude and angle of incremental motion vectors relating to the movement of a vehicle within a predetermined space. A plurality of sensors is used, including a laser beam with corresponding optical position markers placed at known positions and encoders which detect and encode wheel rotation and axle angular position. Vehicle position and angular orientation are determined through vector addition. Shortcomings of this invention include the assumption that wheel diameter is unchanging, that no wheel slip occurs, and that the resolution of wheel encoders is sufficient for the application. The invention requires multiple sensors, and does not provide an alternative means of determining approximate location in the event of primary system failure.
A number of machine vision-based systems exist, especially for vehicle and robot guidance, but most analyze physical surroundings by viewing downward toward floor markings, or horizontally toward local scenery or reflective markers. For example, U.S. Pat. No. 6,728,582 provides a system and method for estimating the position of an object in three dimensions using two machine vision cameras interconnected with a machine vision search tool. A nominal position for each camera's acquired image of the object is determined and a set of uncertainty vectors along each of the degrees of freedom is generated. This method requires viewing multiple objects with multiple cameras in order to make the weighted estimation.
Rotational orientation determination is not present in many position determination methods, and becomes important in applications such as vehicle tracking and vehicle guidance in order for a guidance system to properly direct the vehicle. Considering materials handling applications, goods may be stored in chosen orientations, for example with carton labels aligned in a particular direction or pallet openings aligned to facilitate lift truck access from a known direction. The combination of position determination and angular orientation determination using a single sensor is therefore desired. An improved method and apparatus must reduce or remove the shortcomings of current methods, provide general applicability, and offer high accuracy.
SUMMARY OF THE INVENTION
The present invention provides a method and an apparatus for accurately determining position and rotational orientation within a predefined space, such as a designated area or volume inside a building. The present invention can be employed to determine location in one or two dimensions and rotational orientation in one degree of freedom. It can be applied to stationary and/or mobile objects and can measure the objects position and orientation in real-time as it moves freely within the designated area.
The present invention, which is based on a single optical sensor, overcomes line of sight obscuration problems by providing position markers placed opposite the plane of the object's motion. In the example of a factory, office, or warehouse, the plane of the object's location is typically a floor, and position references are placed overhead.
The present invention provides a reliable and accurate method and apparatus that can be used in many situations. It is suitable for stationary or mobile objects, slow or fast motion, incremental or continuous measurement, indoor or outdoor use, and can serve as the sensory apparatus and method for a guidance system, navigation system, or position monitoring system. While the specific purpose is to track industrial vehicles indoors, it can be applied to track objects of almost any sort, including railcars, heavy equipment, storage containers, people, animals, and so on. It can also be applied to map the location of marked objects in designated areas such as archeological sites, excavations, outdoor storage areas, and mines.
The method of the present invention determines a coordinate position and rotational orientation (i.e., directional heading) of an object within a predefined coordinate space. The method comprises the steps of:
    • providing a plurality of unique position markers having identifying indicia and positional reference indicia thereupon, the markers being arranged at predetermined known X, Y, and Z coordinate positional locations within the coordinate space so that at least one position marker is within view of the object;
    • maintaining a look-up-table comprising actual X, Y, and Z coordinates and rotational orientation of all position markers within the coordinate space;
    • using an image acquisition system comprising a camera mounted on the object, acquiring an image of the at least one position marker within view;
    • processing the image to determine the identity, the coordinate position relative to the object, and the rotational orientation relative to the object of each position marker within view;
    • determining and selecting the position marker nearest to the center of the image;
    • determining an approximate position of the object by retrieving the actual X, Y, and Z coordinates and rotational orientation of the selected position marker from said look-up-table; and
    • using the selected position marker, calculating the coordinate position of the object and the rotational orientation of the object in the coordinate space and storing the position and the rotational orientation information in a memory.
In one embodiment, the step of calculating the position of the object and the rotational orientation of the object in the coordinate space further comprises:
    • identifying two key points in the position marker;
    • defining a line between the two key points;
    • calculating the length of the line;
    • determining the center of the line to define the center of the position marker;
    • determining a vector from the center of the image to the center of the position marker;
    • determining a length and angle of this vector relative to the field of view by plane geometry; and
    • calculating an actual position of the object by correcting the approximate position of the object by using the length and angle of the vector to calculate a position offset,
    • wherein the Z coordinate position of the object is determined from the length of the line between the two key points and the Z coordinate of the position marker, by calculating the proportional distance between the camera and the position marker by scaling the line length into units of actual space.
Position and rotational orientation are determined by acquiring images of position markers which are placed at known locations in or near the coordinate space, i.e., the region of interest. Subsequent image analysis is performed by commercially available machine vision equipment consisting of one or more cameras and image processing system(s). The position and rotational orientation of one or more position markers relative to a camera's view are determined by the machine vision equipment; the position and rotational orientation in “real” space are then computed from machine vision data using a series of programmed instructions which translate the relative positional and rotational orientation data to coordinates expressed in usable units such as feet or meters. Results are stored, displayed, and/or transmitted to another system, such as a post processing system, where data may be used to record object location, to direct vehicle guidance, or for other navigation or control purposes.
Embodiments of the present invention are also directed to an apparatus useful for determining a coordinate position and rotational orientation of an object within a predefined coordinate space. The apparatus comprising:
    • a plurality of unique position markers arranged in at predetermined positional locations within the coordinate space such that at least one position marker is within view of the object, wherein each position marker comprises a substantially planar material imprinted with an asymmetric pattern which encodes the identity and angular orientation of the position marker;
    • an image acquisition system mounted on the object, for acquiring an image of at least one position marker within view;
    • an image processing system for processing pixels in the acquired image to determine the identity of each position marker within view, the position of each position marker relative to the object, the rotational orientation of each position marker relative to the object; and
    • a post processing system for calculating the position of the object and the rotational orientation of the object in the coordinate space.
In some embodiments, the image acquisition system comprises a machine vision system, the machine vision system comprising a camera, a light source, and image capture electronics wherein the light source of the machine vision system is located adjacent to the camera.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 shows the overall system in one embodiment in accordance with the present invention and identifies key elements coordinate reference 1, position markers 2, machine vision camera 4, data processing device 5, vehicles 6, handheld bar code scanner 7, wireless data communications links 8, and illumination source 9.
FIG. 2 illustrates two implementations of coordinate reference 1, showing arrays of two types of position markers: type 2 (employing linear bar code symbols) on the left drawing half, and position markers type 3 (employing two-dimensional bar code symbols) on the right drawing half.
FIG. 3 illustrates details of position marker 2, showing substrate 2 a, label 2 b, and imprinted upon the label geometric position references 12, linear bar code symbol 11, and human readable marker identification 10.
FIG. 4 defines key points A and B, point C (the midpoint of line AB which defines the center of the symbol), and dimension D of position marker 2.
FIG. 5 shows position marker 2 rotated counterclockwise with respect to Cartesian coordinate axes X and Y and defines angle BCE as the angle of rotation.
FIG. 6 shows a camera's field of view with one entire position marker and one partial position marker in view. The distance between the center of the field of view (point O) and the center of the position marker (point C) is defined as line segment OC. Angle XOC is defined as the radial angle from the X axis to the position marker.
FIG. 7 shows a sample Look-Up-Table containing position marker data.
FIG. 8 presents a high level software flow diagram for the general solution using marker type 2.
FIG. 9 presents a software flow diagram for image processing and feature extraction steps.
FIG. 10 shows a software flow diagram for expected position and rotational orientation determination.
FIG. 11 shows a software flow diagram for the calculation of actual position and rotational orientation.
FIG. 12 shows position marker type 3 with a two-dimensional bar code symbol 13, substrate 3 a, label 3 b, and human readable text 10.
FIG. 13 defines key points J, K, and L of position marker 3.
FIG. 14 defines point N (the midpoint of line JK), which defines the center of the symbol, and dimension M of position marker 3. Angle JLP indicates the rotational angle with respect to Cartesian coordinate axes X and Y.
FIG. 15 shows a camera's field of view with one entire position marker and one partial position marker in view. The distance between the center of the field of view (point O) and the center of the position marker (point N) is defined as line segment ON. Angle XON is defined as the radial angle from the X axis to the position marker.
FIG. 16 shows a sample Look-Up-Table containing position marker data.
FIG. 17 presents a software flow diagram for image processing and feature extraction steps for marker type 3.
FIG. 18 shows a software flow diagram for expected position and rotational orientation determination.
FIG. 19 shows a software flow diagram for the calculation of actual position and rotational orientation.
FIG. 20 shows an alternate embodiment whereby the machine vision camera is placed overhead and position markers are applied to the vehicle.
FIG. 21 shows an arrangement of multiple overhead cameras tracking multiple vehicles.
FIG. 22 shows a software flow diagram for the embodiments illustrated in FIGS. 20 and 21.
DETAILED DESCRIPTION
The present invention provides a novel method of determining position and rotational orientation through the following steps:
1. The determination of position and rotational orientation in a designated area is accomplished by contemporary machine vision equipment using a coordinate reference, comprising a plurality of unique position markers, which is placed within or near to the designated area or volume. Sufficient position markers are provided so that at least one position marker of the coordinate reference is visible to the determination system from each and every location within the designated area or volume.
2. Machine readable symbols, such as one-dimensional or two-dimensional barcodes, encode the identity of each position marker of the coordinate reference, allowing bar code scanning devices 7 (FIG. 1) to read the identities of the symbols in addition to, or in lieu of the current invention's automated system. Position data in human readable form (text) may also be imprinted, attached, or otherwise affixed to the position markers if desired. Printed text allows determination of approximate location by simply viewing the coordinate reference and reading the text on the nearest position marker.
3. Machine recognizable symbols are arranged on the position markers of the coordinate reference at predetermined positions, allowing machine vision technology to determine position by analyzing the shapes and symbols on the position markers. Exact position coordinates and rotational orientation are determined through computer programmed instructions which are based upon geometric analysis of acquired image data.
4. In one embodiment, two-dimensional non-symmetric, non-concentric barcode symbols are utilized to serve the dual purpose of machine readable position location codes and geometric position markers.
Coordinate reference 1 is not required for the invention, but may provide physical support for position markers if no other structures such as ceilings, beams, walls, etc. are available for direct attachment of the markers. The coordinate reference may be constructed of any of several air-permeable or perforated materials (example: netting) or solid materials (example: plastic sheet). Netting examples include fish net, basketball net, fence net, screen (window screen, tent screen), and mesh (examples: garment lining, landscaping mesh). Solid materials include sheet or webs such as polyolefin film, non-woven synthetic material, and paper. Perforated or permeable materials offer the advantage of allowing air to pass through, for example, to accommodate indoor ventilation. Perforated, transparent, and translucent materials offer the advantage of allowing light to pass through the coordinate reference, for example to allow room lighting to be transmitted. Solid materials, which may also be perforated (example: paper with punched holes), may be used and may be opaque, translucent, or transparent, depending on lighting and ventilation requirements for the application. Either solid or perforated materials can be readily used to implement the invention. The coordinate reference is sized to match the predefined space, volume, or area to be controlled. The purpose of the coordinate reference 1 is to simply provide a convenient surface on which a plurality of unique position markers 2, 3 can be imprinted, attached or affixed. Lacking a coordinate reference, position markers may be applied directly to a ceiling, roof, wall, beam, or other structure, or may be suspended, supported, or attached to nearby structure.
The coordinate reference may be supported by building structure, for example, by factory or warehouse ceiling beams if the coordinate reference is to be suspended overhead. Free standing fixtures or other fixed structure may be used for other orientations; for example, the coordinate reference may be attached to a wall parallel and opposite to a wall on which objects are desired to be tracked. In some cases, position markers may be attached directly to building structures without the necessity of affixing them first to a secondary surface.
Position markers 2 and 3 are constructed from any material on which printing can be done directly or can be applied, as a label. Mechanical sturdiness is an important factor for assuring marker longevity, and many materials offer adequate printability and sturdiness. Paper, sheet goods, plastic sheeting, cardboard, metal, and other common materials are suitable. The markings can be dark on a light or transparent background, light on a dark or opaque background, or of one or more colors. Marker attachment to the coordinate reference may be by fasteners such as screws, clips, or wire ties, adhesives such as glue or pressure sensitive label adhesive. Alternatively, the position markers can be imprinted directly on the coordinate reference using silkscreen, lithographic, or offset printing methods. The coordinate reference may be substantially planar or non-planar. It is necessary only that each marker has a unique identity and that the position, orientation, and size of each marker relative to the designated area is known.
Position markers are imprinted upon or attached to the coordinate reference 1 in a prescribed pattern; for example, in rows and columns corresponding to a desired coordinate plan for the designated area. Position marker 2 shown in FIG. 3 contains three components; text 10 to aid manual identification of each grid location (example: “AA01”=Row “AA”, Column “01”), a one-dimensional (linear) barcode 11 which encodes the marker location “AA01” in any of several common bar code symbologies; and geometric position references 12 which serve as position and angular orientation references, or optical targets, for the machine vision system.
It may be desirable in certain instances for the position markers to be read by humans, or to be scanned by bar code scanners. These alternative methods offer assurance that position information can be determined even though the automated method of the present invention is inoperative, for example, during a power failure. Linear bar codes 11 in position marker 2 are selected for these implementations.
The position marker 3 of FIGS. 12 and 13 provides information equivalent to that of position marker 2, but does so with a single graphic; in this case, a two-dimensional bar code symbol. The marker is comprised of text 10, and barcode 13, which serves the dual purpose of encoding the marker identity and, due to its non-symmetric form, serving as a position and angular orientation reference.
Contemporary machine vision technology is utilized to capture and process images of the coordinate reference and position markers. Offering sophisticated image processing capabilities such as presence or absence detection, dimensional measurement, and object shape identification, machine vision systems are typically comprised of a video camera, a computing device, and a set of software routines. Machine vision equipment is commercially available and suitable for most environments. In order to develop a machine vision application, the user chooses certain subroutines, combines them into a sequence or procedure, and stores the procedure in the memory or storage device of the machine vision computing device. The present invention includes a set of software instructions that calls certain procedures to capture images, adjust images for readability, analyze images to detect features, and measure detected features to determine geometric data such as object size or location within the camera's field of view. Output data are produced at the conclusion of each procedure and may be stored or transferred to another device.
The present invention provides a second computing device to (a) calculate the object's position with high precision, (b) calculate the object's rotational angle with high precision, (c) compensate for position marker installation inconsistencies, and (d) translate position and orientation values into convenient units.
DESCRIPTION OF THE PREFERRED EMBODIMENT
Referring to FIG. 1, the preferred embodiment of the invention will now be described in detail. The coordinate reference is made from thermoplastic flat net such as CintoFlex “D”, available from Tenax Corporation. Designed to prevent deer from entering highways, the material is lightweight, strong, and inexpensive. The net is cut to the dimensions sufficient to cover the area of interest; for example, it can be cut to the size of a storage area. Multiple nets can be adjoined side by side to cover large areas. Alternatively, the net can be cut into strips wide enough to support rows of position markers, whereby each strip spans across a particular area within a building, and the strips are suspended in parallel with one another.
Position markers 2 are fabricated of two components; a label 2 b and a backing plate 2 a. Labels are printed using common bar code label printers such as the Intermec Model 3600 Thermal/Thermal Transfer printer. Label stock such as Duratran II Thermal Transfer Label Stock, part No. E06175, also available from Intermec Corporation, is available from many suppliers. Bar code symbols, each containing a unique identification encoded in 1-D bar code symbology are printed on the label stock, along with human readable text. Bar codes of most standard formats are usable; for example, Code 39, Code 128, CODABAR, UCC/EAN128, and Interleaved Two-Of-Five (ITF) codes are common. The labels are then adhesively affixed to a stiffer substrate, or backing plate, 2 a, to add mechanical strength. Many materials can be used for backing plates, but for its low cost and ease of use, white 0.030 inch thick PVC (polyvinyl chloride) is a good choice. The backing plate is sized larger than the label to provide an optical quiet zone around each bar code symbol. Attachment of the backing plate to the coordinate reference net can be done in many ways, using staples, glue, weldments, etc., but is preferably done with plastic wire ties. Attachment is done by inserting tie into holes which have been punched or drilled in the backing plates, and threading the ties through the net.
FIG. 1 illustrates a typical embodiment in a warehouse, where materials are stored on the floor. Coordinate reference 1, based on the net/screen/mesh design is suspended from overhead, and is placed sufficiently high above the working area so as not to interfere with operations. Suspension is provided by mechanical supports such as cables, wire, or building structure (not shown), or the reference is attached directly to the ceiling, whereupon the material assumes a substantially planar form. The semi-open structure allows much light to pass from overhead light fixtures to the work area, and air to flow freely for heating and ventilation considerations.
Position markers 2 on coordinate reference 1 identify coordinate locations. After being installed in the warehouse facility, the markers remain stationary. Each marker therefore corresponds to a particular location on the warehouse floor, and a database of these locations is created and stored in a computational device (digital computer) 5. The data base may be generated in advance of coordinate reference installation, and populated with expected values. It may be modified after installation if a physical survey determines that discrepancies exist between expected values and actual values for marker locations, rotation angles, or dimensions. Markers commonly share uniform dimensions, but some applications may require markers of different sizes. Image analysis routines are presented to correct for varied marker size or varied distance from the camera to the markers.
Vehicles 6 have affixed to them machine vision cameras 4. Illumination source 9 may be required for dark operations such as in dimly illuminated warehouses. The light source may be a spotlight, floodlight, strobe, LED, or other conventional source. The preferred embodiment utilizes room lighting. Computer 5 can reside on-board as shown on the fork lift truck of FIG. 1, or be out boarded as shown on the van. Standard commercial wireless data communication network equipment 8 provides data transmission between vehicles not equipped with on-board computers and a computer 5 stationed remotely.
In this example, the vehicles have freedom of motion in two dimensions within the operating area; therefore, the invention embraces two-dimensional analysis, plus single degree-of-freedom rotation (heading) determination.
The position and rotational orientation determination system is active at all times when the vehicle is within the designated area beneath position reference 1. Camera images may be captured continuously, or on command, such as when the vehicle stops, or at a time chosen by the operator. When the camera 4 captures an image of the overhead position reference 1 the image is transmitted to the machine vision system computational device 5 for analysis.
Image Analysis
The method of the preferred embodiment utilizes callable vendor-supplied subroutines to analyze position markers and store data obtained from the analysis. Rotational orientation and position are calculated from these data and stored or transferred to other devices.
The preferred embodiment applies a commercial machine vision system such as Model 5100 or Model 5400 from Cognex, Incorporated. “In-Sight Explorer™” software provided with this system offers a wide array of feature extraction, mathematical, geometric, object identification, and barcode symbol decoding subroutines.
The following functional steps analyze the image within the field of view, identify position markers, decode the position markers' encoded position information, calculate X-Y coordinates in pixel space, and convert the results to actual position and heading.
Image Processing—Brief Description
FIG. 8 presents a condensed flow diagram. The process produces four separate sets of data: marker ID 300, approximate position 400, expected position and heading 500 and actual position and heading 600.
Upon internal or external command, an image is captured 110 by the machine vision camera and stored into its memory. Analysis begins by locating 120 a readable position marker image (image in which the bar code can be decoded) within the field of view. In normal circumstances and by design, at least one position marker will be present within the field of view. Once a marker has been located, the marker identification is decoded 130 and the data is stored in the machine vision system memory 4 and is available as an output 300. Marker positions are stored in a look-up table (FIG. 7) in computer 5, and the table can be accessed to return the approximate camera position 400. In other words, by knowing that the camera is viewing a particular marker we can place the camera within the approximate region of that marker.
Markers may be directly encoded with position information, or they may be serially encoded with non-meaningful “license plate” numbers. Direct encoding allows the decoded ID to translate directly into real coordinates; for example, marker 100250 may be encoded to mean “100 feet south, 250 feet west”. Approximate position 400 is calculated in this manner, based on decoded marker ID and a transformation scalar to convert pixels into feet. Serial encoding may be chosen whereby the ID has no inherent meaning and a look-up table contains references to the actual position.
The image is next analyzed 150 to determine the relative location, orientation, and size of the marker within the field of view. The marker's angular orientation and its azimuth from the center of the field of view are calculated and stored in degrees. Expected position and orientation can then be calculated 160 using plane geometry for markers that directly encode position. This step cannot be done for serialized markers unless the look-up table of FIG. 7 is accessed. Expected position and heading 500 assume the marker's position and orientation are exactly where the encoded value places it. Actual values may differ if the marker is installed slightly offset its intended location or orientation.
Marker ID, relative position within the field of view, angular orientation, and marker dimensions are passed to a second processor 5. The decoded ID serves as a key to access true marker position data 170, which is obtained from a lookup table in the second computer. The marker's actual position is then calculated 180 from the marker's position within the field of view; that is, how far from the center of the field of view, and at what azimuth, as in step 160, but using actual positional and orientation values. The results are transformed from pixels into real dimensions such as feet or meters. The results 600 can be saved and/or conveyed to other devices for storage, presentation, or other purpose. The cycle repeats 200 once a full determination has been made.
A complete description of image processing steps follows.
Image Capture and Marker Identification (100, 110, 120, 130, and 300)
Referring to FIGS. 8, 9, 10, and 11, the following steps take place within the machine vision software.
The machine vision camera 4 continuously, or on command, captures analog and/or digital images of the position markers 2 of the coordinate reference 1. One or more position markers 2 are partially or fully visible within the camera's field of view at any given time. Once an image is captured, the software analyzes it as follows:
Image data 20 is manipulated by preprocessing routines 21 to enhance image features such as sharpness, contrast, and brightness. The resulting processed image is tested 22 for image brightness and contrast. The image is returned for additional processing 23 if not adequate for interpretation. Once the image has passed preprocessing, it is analyzed 24 to locate all position markers. This stage determines whether single or multiple position markers appear within the field of view, and superfluous image data such as position marker printed text and background objects and the coordinate reference net are ignored. Position markers found fully visible within the field of view are analyzed for readability 25 to determine if the bar code associated with the marker can be decoded. If a single marker is found, selected image data are passed to a decoder 27; if multiple markers are present, image data are passed to a readability test 26, which determines which marker is most readable and passes the selected image data to the decoder 27. Alternatively, the readability test may select the marker closest to the center of the image and pass that image data to the decoder 27. Decoder 27 “reads” the encoded unique identification code of the position marker and returns alphanumeric data which are stored as decoded position marker identification data 300. An example of an encoded one-dimensional bar coded position marker is shown in FIG. 4. Selected image data for a single marker are also passed to position marker key point locator 29 which analyzes image data to locate key points A, B, and C of the position marker symbol (FIG. 7). Key points are then stored 30 as pixel coordinates.
In the case of position marker 2 of FIG. 4, having a one-dimensional barcode, the locating mechanism 24 first finds bar codes within the field of view; then steps 25 through 27 proceed to decode the barcode. “Blobs” (contiguous dark areas on light backgrounds) nearest to the chosen bar code are located, and the centers of the blobs are determined. Since one blob is always larger than the other for any given marker, the areas of the two are calculated and compared. The key points for the position marker are defined to be the centers of the circular position references 12.
Approximate Position Determination (140, 400)
Referring to FIG. 10, the following steps begin after completion of image processing and feature extraction steps. Marker identification can be translated directly into real X and Y position data for markers that are directly encoded. As earlier illustrated, marker ID 100250 might translate directly as “100 feet south and 250 feet west”. Having this marker within the field of view implies that the camera (object) is somewhere near this point, but not necessarily exactly at this point. With markers spaced ten feet apart, the camera and object would probably lie within half-marker spacing, or five feet. Object orientation is not determined.
Expected Position and Orientation Determination (160, 500)
Referring to FIGS. 5, 6, and 10, and applying only to directly encoded markers, a geometric analysis of the marker's position and rotation relative to the field of view can more accurately determine the camera's position and orientation. Pixel coordinates of Key Points B and C, 30, are used to calculate angle BCE, 34, the rotation angle of the position marker relative to the field of view.
Angle BCE is illustrated in FIG. 5 and shown in the camera's field of view in FIG. 6. X and Y values of pixel coordinates A and C, 30, are summed and divided by two (37) to establish Point E (FIG. 10), the midpoint of line segment AC, and the center of the position marker. Point E coordinates are used to calculate: (a) angle XOC, FIG. 11, the radial angle between the center of the image and the center of the position marker; and (b) the length of line segment OC, which is equal to the radial distance from the center of the image (center of the camera), Point O, to the center of the position marker, Point E. Once these two values have been established, it is possible to calculate 40 a more accurate X, Y camera position using plane geometry. The “expected position” is therefore an accurate calculation based on the expected position and orientation of the marker.
Actual Position and Orientation Determination (170, 180, 600)
The Position Marker Look-Up Table 31 (FIG. 7) is a database containing actual X, Y, and Z coordinates and rotational orientations that have been measured and recorded for all position markers at the time of the coordinate reference installation. Coordinate values are recorded in conventional units, such as feet, meters and degrees. In this embodiment, and referring to FIG. 2, the coordinate reference (leftside of drawing) includes markers AA01, AA02, etc. X values correspond in the example to the north/south coordinate; Y values to east/west coordinate; Z values to marker height above the floor, θ values correspond to the difference between the marker's rotational angle and its nominal angle, and the size value records the marker's dimensions referenced to the length of line segment AB.
Actual orientation is calculated 44 as the sum of the expected orientation and the look-up table value of θ. Actual position is recalculated 46 exactly as in steps 150 and 160, but using look-up table data instead of expected (assumed) X and Y data.
Apparent marker size 43 is applied as an adjustment factor in calculation 46 for markers whose dimensions differ from nominal.
Decoded marker ID 300 is used in FIG. 11 to search look-up table 31. The results of this calculation are stored in memory. To determine the Z coordinate and position, Key Points A and B are used to calculate the length of Line Segment AB of the image. Since the distance AB on the position marker 3 is known and the focal length of the lens of the camera 4 is known, the distance from the camera 4 to the position marker can be determined from the ratio of the length of Line Segment AB in the image to the distance AB on the position marker 3. With the Z coordinate of the position marker 3 also known, the Z coordinate of the object may be readily calculated. The Z coordinates are stored in memory.
The final step is the calculation and combination 46 of actual rotational orientation and X and Y coordinates into a single unit of data which can be stored in local memory or transmitted to other devices. Rotational orientation and position data derived from the image processing steps may be optionally transformed into alternate units to indicate specific regions such as a zones, sectors, or areas.
Description of the Second Embodiment
Referring to FIGS. 1 and 2, a second embodiment will now be described. Steps omitted are assumed to be unchanged from the preferred embodiment. This embodiment utilizes two-dimensional bar codes. Coordinate reference 1 consists of position markers 3 (FIG. 12), which are fabricated of labels 3 b and substrates 3 a. Bar code symbols, each containing a unique identification encoded in two-dimensional bar code symbology are printed on the label stock, along with human readable text. Bar codes of standard formats can be used including DataMatrix, Code One, PDF417, Array Tag, and QR Code. DataMatrix symbols are chosen in this embodiment for their ubiquitous usage, error correction robustness, and well developed suite of image processing software available in commercial machine vision systems.
Image Capture and Marker Identification (100, 110, 120, 130, and 300)
Referring to FIGS. 1, 8, 17, 18, and 19, the following steps take place. The machine vision camera 4 continuously, or on command, captures analog and/or digital images 20 of position markers 3. At least one marker is fully visible within the camera's field of view at any given time. Once an image is captured, the software analyzes it as in the preferred embodiment for steps 21 through 27. The chosen marker is analyzed to locate key points J, K, and L, which are defined in FIG. 13. Key point coordinates are stored 30 for each point, and marker ID is decoded and available as an output 300.
Approximate Position Determination (140, 400)
Referring to FIG. 18, marker identification can be translated directly into real X and Y position data for markers that are directly encoded. Object orientation is not determined.
Expected Position and Orientation Determination (160, 500)
Geometric analysis of the marker's position and rotation relative to the field of view can more accurately determine the camera's position and orientation as in the earlier example. Pixel coordinates of Key Points J and L, 30, are used to calculate angle JLP, 34, the rotation angle of the position marker relative to the field of view. Angle JLP is illustrated in FIG. 14 and shown in the camera's field of view in FIG. 15. X and Y values of pixel coordinates J and K, 30, are summed and divided by two (37) to establish Point N (FIG. 14), the midpoint of line segment JK, and the center of the position marker. Point N coordinates are used to calculate (a) angle XON (FIG. 15) the radial angle between the center of the image and the center of the position marker; and (b) the length of line segment ON, which is equal to the radial distance from the center of the image (center of the camera), Point O, to the center of the position marker, Point N. Once these two values have been established, plane geometry is used to calculate 40 a more accurate X, Y camera position. The “expected position” is therefore an accurate calculation based on the expected position and orientation of the marker.
Actual Position and Orientation Determination (170, 180, 600)
Position Marker Look-Up Table 31 (FIG. 16) is the same as described earlier. Actual orientation is calculated 44 as the sum of the expected orientation and the look-up table correction value. Actual position is recalculated 46 exactly as in steps 150 and 160, but using look-up table data instead of expected (as decoded) X and Y data. Apparent marker size 43 is applied as an adjustment factor in calculation 46 for markers whose dimensions differ from nominal.
The final step is the combination 46 of actual rotational orientation and X and Y coordinates into a single unit of data which can be stored in local memory or transmitted to other devices. Rotational orientation and position data derived from the image processing steps may be optionally transformed into alternate units to indicate specific regions such as a zones, sectors, or areas.
Description of the Third Embodiment
The invention can operate in a second physical arrangement wherein the camera is fixed in space and the markers are affixed to movable objects. FIG. 20 presents an application example, where machine vision camera 4 is mounted overhead and a position marker 2 or 3 is affixed to a vehicle. The camera views a predetermined area as vehicle 6 moves about the area. The marker is within the field of view so long as the vehicle remains within the predetermined area. Image processing steps are identical to embodiment 1 and 2, with the exception that camera coordinates in real space are used as a reference point, and object coordinates are calculated from image data. Image analysis steps are identical to earlier examples, but the transformation of image data into position data differs; in this arrangement the system determines where a viewed object is located instead of determining where the system itself is located. Orientation is calculated directly as before.
An illustration of the second arrangement is presented in FIG. 21, wherein a plurality of machine vision cameras tracks vehicles. Three predetermined coverage zones are shown, each covered by a separate machine vision camera. The drawing illustrates zones of no coverage, where a vehicle is not detected by the system, and zones of overlapping coverage, where multiple cameras detect and cross-check vehicle location and orientation. Computer 5 is connected to cameras via standard wired or wireless networks and performs the same functions described above for each camera, but in addition, records the location of all vehicles within the three areas.
The important difference between this arrangement and embodiments 1 and 2 is that each image is analyzed for all position markers, and all position markers are processed. Therefore, image processing (FIG. 22) ignores image enhancement steps 22, 23 and best marker determination step 26, and proceeds directly from step 25 to steps 27 and 29.
The location and orientation of all markers (e.g. vehicles) in the plurality of fields of view can be stored, graphically displayed, or transmitted to other systems such for purposes of fleet management, collision avoidance, and so forth. The invention can keep track of the last known position of each vehicle; vehicle speed can be calculated, and predictions can be made for vehicle location in areas of no coverage and for impending collisions between vehicles.

Claims (10)

1. A method of determining a coordinate position and rotational orientation of an object within a predefined coordinate space, the method comprising:
providing a plurality of unique position markers having identifying indicia and positional reference indicia thereupon, the markers being arranged at predetermined known X, Y, and Z coordinate positional locations within the coordinate space so that at least one position marker is within view of the object;
maintaining a look-up-table comprising actual X, Y, and Z coordinates and rotational orientations of all position markers within the coordinate space;
using an image acquisition system comprising a camera mounted on the object, acquiring an image of the at least one position marker within view;
processing the image to determine the identity, the coordinate position relative to the object, and the rotational orientation relative to the object of each position marker within view;
determining and selecting the position marker nearest to the center of the image;
determining an approximate position of the object by retrieving the actual X, Y, and Z coordinates and rotational orientation of the selected position marker from said look-up-table; and
using the selected position marker, calculating the coordinate position of the object and the rotational orientation of the object in the coordinate space and storing the position and the rotational orientation information in a memory.
2. The method of claim 1, wherein the step of calculating the position of the object and the rotational orientation of the object in the coordinate space further comprises:
identifying two key points in the position marker;
defining a line between the two key points;
calculating the length of the line;
determining the center of the line to define the center of the position marker;
determining a vector from the center of the image to the center of the position marker;
determining a length and angle of this vector relative to the field of view by plane geometry; and
calculating an actual position of the object by correcting the approximate position of the object by using the length and angle of the vector to calculate a position offset,
wherein the Z coordinate position of the object is determined from the length of the line between the two key points and the Z coordinate of the position marker, by calculating the proportional distance between the camera and the position marker by scaling the line length into units of actual space.
3. The method of claim 2, wherein the position markers are arranged substantially in a plane defined by the Z coordinate of the coordinate space.
4. The method of claim 2, wherein the position markers are arranged at different Z coordinate positions.
5. An apparatus useful for determining a coordinate position and rotational orientation of an object within a predefined coordinate space, the apparatus comprising:
a plurality of unique position markers arranged at predetermined positional locations within the coordinate space such that at least one position marker is within view of the object, wherein each position marker comprises a substantially planar material imprinted with an asymmetric pattern which encodes the identity and angular orientation of the position marker;
an image acquisition system mounted on the object, for acquiring an image of at least one position marker within view;
an image processing system for processing pixels in the acquired image to determine the identity of each position marker within view, the position of each position marker relative to the object, the rotational orientation of each position marker relative to the object; and
a post processing system for calculating the position of the object and the rotational orientation of the object in the coordinate space.
6. The apparatus of claim 5, wherein the image acquisition system comprises a machine vision system, the machine vision system comprising a camera, a light source, and image capture electronics wherein the light source of the machine vision system is located adjacent to the camera.
7. The apparatus of claim 6, wherein the light source is pulsed.
8. The apparatus of claim 6, wherein the light source is continuous.
9. The apparatus of claim 6, wherein the light source emits a narrow wavelength band of illumination.
10. The apparatus of claim 6 wherein the light source comprises one or more light emitting diodes (LEDs).
US12/960,728 2004-12-14 2010-12-06 Method and apparatus for determining position and rotational orientation of an object Active US8196835B2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
US12/960,728 US8196835B2 (en) 2004-12-14 2010-12-06 Method and apparatus for determining position and rotational orientation of an object

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US63581304P 2004-12-14 2004-12-14
US11/292,463 US7845560B2 (en) 2004-12-14 2005-12-03 Method and apparatus for determining position and rotational orientation of an object
US12/960,728 US8196835B2 (en) 2004-12-14 2010-12-06 Method and apparatus for determining position and rotational orientation of an object

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
US11/292,463 Continuation US7845560B2 (en) 2004-12-14 2005-12-03 Method and apparatus for determining position and rotational orientation of an object

Publications (2)

Publication Number Publication Date
US20110121068A1 US20110121068A1 (en) 2011-05-26
US8196835B2 true US8196835B2 (en) 2012-06-12

Family

ID=36588368

Family Applications (2)

Application Number Title Priority Date Filing Date
US11/292,463 Active 2029-06-21 US7845560B2 (en) 2004-12-14 2005-12-03 Method and apparatus for determining position and rotational orientation of an object
US12/960,728 Active US8196835B2 (en) 2004-12-14 2010-12-06 Method and apparatus for determining position and rotational orientation of an object

Family Applications Before (1)

Application Number Title Priority Date Filing Date
US11/292,463 Active 2029-06-21 US7845560B2 (en) 2004-12-14 2005-12-03 Method and apparatus for determining position and rotational orientation of an object

Country Status (3)

Country Link
US (2) US7845560B2 (en)
EP (1) EP1828862A2 (en)
WO (1) WO2006065563A2 (en)

Cited By (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140218532A1 (en) * 2012-08-06 2014-08-07 Cloudparc, Inc. Defining a Handoff Zone for Tracking a Vehicle Between Cameras
US20140257943A1 (en) * 2012-08-06 2014-09-11 Cloudparc, Inc. Tracking Speeding Violations and Controlling Use of Parking Spaces Using Cameras
US20140368443A1 (en) * 2013-06-14 2014-12-18 Agilent Technologies, Inc. System for Automating Laboratory Experiments
US9354070B2 (en) 2013-10-31 2016-05-31 Crown Equipment Corporation Systems, methods, and industrial vehicles for determining the visibility of features
US9489839B2 (en) 2012-08-06 2016-11-08 Cloudparc, Inc. Tracking a vehicle using an unmanned aerial vehicle
US9547079B2 (en) 2014-02-06 2017-01-17 Fedex Corporate Services, Inc. Object tracking method and system
US9599480B2 (en) 2015-03-06 2017-03-21 Umm Al-Qura University Vehicle localization and transmission method and system using a plurality of communication methods
US9864371B2 (en) 2015-03-10 2018-01-09 John Bean Technologies Corporation Automated guided vehicle system
US9886036B2 (en) 2014-02-10 2018-02-06 John Bean Technologies Corporation Routing of automated guided vehicles
US10511926B2 (en) 2007-10-17 2019-12-17 Symbol Technologies, Llc Self-localization and self-orientation of a ceiling-mounted device
US10589931B2 (en) 2016-09-30 2020-03-17 Staples, Inc. Hybrid modular storage fetching system
EP2923335B1 (en) 2012-11-22 2020-03-18 R-Biopharm AG Test strip and methods and apparatus for reading the same
US10683171B2 (en) 2016-09-30 2020-06-16 Staples, Inc. Hybrid modular storage fetching system
US10780930B1 (en) * 2018-02-20 2020-09-22 Zoox, Inc. Worm gear drive unit interface and assembly methods
US10803420B2 (en) 2016-09-30 2020-10-13 Staples, Inc. Hybrid modular storage fetching system
US10960939B1 (en) 2018-02-20 2021-03-30 Zoox, Inc. Worm gear drive unit interface and assembly methods
US11084410B1 (en) 2018-08-07 2021-08-10 Staples, Inc. Automated guided vehicle for transporting shelving units
US11119487B2 (en) 2018-12-31 2021-09-14 Staples, Inc. Automated preparation of deliveries in delivery vehicles using automated guided vehicles
US11124401B1 (en) 2019-03-31 2021-09-21 Staples, Inc. Automated loading of delivery vehicles
US20210312661A1 (en) * 2018-12-28 2021-10-07 Panasonic Intellectual Property Management Co., Ltd. Positioning apparatus capable of measuring position of moving body using image capturing apparatus
US11180069B2 (en) 2018-12-31 2021-11-23 Staples, Inc. Automated loading of delivery vehicles using automated guided vehicles
US11590997B1 (en) 2018-08-07 2023-02-28 Staples, Inc. Autonomous shopping cart
US20230092401A1 (en) * 2017-11-17 2023-03-23 Divine Logic, Inc. Systems and methods for tracking items
US11630447B1 (en) 2018-08-10 2023-04-18 Staples, Inc. Automated guided vehicle for transporting objects
US11946771B2 (en) 2020-04-01 2024-04-02 Industrial Technology Research Institute Aerial vehicle and orientation detection method using same

Families Citing this family (311)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8032276B2 (en) 2004-12-07 2011-10-04 Geotab, Inc. Apparatus and method for optimally recording geographical position data
EP1828862A2 (en) * 2004-12-14 2007-09-05 Sky-Trax Incorporated Method and apparatus for determining position and rotational orientation of an object
US8341848B2 (en) * 2005-09-28 2013-01-01 Hunter Engineering Company Method and apparatus for vehicle service system optical target assembly
US8381982B2 (en) * 2005-12-03 2013-02-26 Sky-Trax, Inc. Method and apparatus for managing and controlling manned and automated utility vehicles
US10878646B2 (en) 2005-12-08 2020-12-29 Smartdrive Systems, Inc. Vehicle event recorder systems
US8239083B2 (en) 2006-01-18 2012-08-07 I-Guide Robotics, Inc. Robotic vehicle controller
US7953526B2 (en) * 2006-01-18 2011-05-31 I-Guide Robotics, Inc. Robotic vehicle controller
DE102006004197A1 (en) * 2006-01-26 2007-08-09 Klett, Rolf, Dr.Dr. Method and device for recording body movements
US20070213869A1 (en) * 2006-02-08 2007-09-13 Intermec Ip Corp. Cargo transporter with automatic data collection devices
US8996240B2 (en) 2006-03-16 2015-03-31 Smartdrive Systems, Inc. Vehicle event recorders with integrated web server
DE102006044645A1 (en) * 2006-09-21 2008-04-10 Gottwald Port Technology Gmbh Method and system for determining the position and orientation of an unmanned vehicle and corresponding vehicle
US7839431B2 (en) * 2006-10-19 2010-11-23 Robert Bosch Gmbh Image processing system and method for improving repeatability
DE102006050850B4 (en) * 2006-10-27 2009-01-02 Locanis Ag Method and device for measuring distance
WO2008057504A2 (en) * 2006-11-06 2008-05-15 Aman James A Load tracking system based on self- tracking forklift
US8649933B2 (en) 2006-11-07 2014-02-11 Smartdrive Systems Inc. Power management systems for automotive video event recorders
US8989959B2 (en) 2006-11-07 2015-03-24 Smartdrive Systems, Inc. Vehicle operator performance history recording, scoring and reporting systems
US8868288B2 (en) 2006-11-09 2014-10-21 Smartdrive Systems, Inc. Vehicle exception event management systems
JP4833105B2 (en) * 2007-02-06 2011-12-07 富士通フロンテック株式会社 Information terminal device, store information providing device, store information providing method, and store information providing program
ES2558022T3 (en) * 2007-09-12 2016-02-01 Pepperl + Fuchs Gmbh Procedure and device for determining the position of a vehicle, computer program and computer program product
KR101461185B1 (en) * 2007-11-09 2014-11-14 삼성전자 주식회사 Apparatus and method for building 3D map using structured light
KR100939731B1 (en) * 2007-12-17 2010-01-29 한국전자통신연구원 Terminal and method for measuring position using location of position identifying tag
US8210435B2 (en) * 2008-01-14 2012-07-03 Sky-Trax, Inc. Optical position marker apparatus
US8565913B2 (en) * 2008-02-01 2013-10-22 Sky-Trax, Inc. Apparatus and method for asset tracking
US9495386B2 (en) 2008-03-05 2016-11-15 Ebay Inc. Identification of items depicted in images
WO2009111047A2 (en) 2008-03-05 2009-09-11 Ebay Inc. Method and apparatus for image recognition services
US9171484B2 (en) * 2008-03-06 2015-10-27 Immersion Corporation Determining location and orientation of an object positioned on a surface
US8800859B2 (en) 2008-05-20 2014-08-12 Trimble Navigation Limited Method and system for surveying using RFID devices
US8348166B2 (en) * 2008-05-20 2013-01-08 Trimble Navigation Limited System and method for surveying with a barcode target
US8500005B2 (en) 2008-05-20 2013-08-06 Trimble Navigation Limited Method and system for surveying using RFID devices
US20110068164A1 (en) * 2009-09-24 2011-03-24 Trimble Navigation Limited Method and Apparatus for Barcode and Position Detection
WO2009146359A1 (en) 2008-05-28 2009-12-03 Illinois Tool Works Inc. Welding training system
US8346468B2 (en) * 2008-07-08 2013-01-01 Sky-Trax Incorporated Method and apparatus for collision avoidance
JP5432176B2 (en) * 2008-11-21 2014-03-05 テルモ株式会社 Connector
JP5168124B2 (en) * 2008-12-18 2013-03-21 富士通株式会社 Image marker adding apparatus, method, and program
US20120172711A1 (en) * 2009-02-04 2012-07-05 Marshall Kerr Injectable Vascular Access Port with Discernable Markers for Identification
US20110050903A1 (en) * 2009-04-08 2011-03-03 Topcon Positioning Systems, Inc. Method for determining position and orientation of vehicle trailers
US20110039573A1 (en) * 2009-08-13 2011-02-17 Qualcomm Incorporated Accessing positional information for a mobile station using a data code label
US9488466B2 (en) * 2009-09-24 2016-11-08 Trimble Navigation Limited System and method for tracking objects
US8988505B2 (en) 2009-10-20 2015-03-24 Imris Inc Imaging system using markers
US9164577B2 (en) * 2009-12-22 2015-10-20 Ebay Inc. Augmented reality system, method, and apparatus for displaying an item image in a contextual environment
US8855929B2 (en) * 2010-01-18 2014-10-07 Qualcomm Incorporated Using object to align and calibrate inertial navigation system
DE102010008957A1 (en) * 2010-02-19 2011-08-25 FusionSystems GmbH, 09125 Method for contactless position determination of objects e.g. rail vehicles, in industrial application, involves using visible or non visible light and surface sensor for sensory detection of coding information of objects
CN102449427A (en) * 2010-02-19 2012-05-09 松下电器产业株式会社 Object position correction device, object position correction method, and object position correction program
US8508590B2 (en) * 2010-03-02 2013-08-13 Crown Equipment Limited Method and apparatus for simulating a physical environment to facilitate vehicle operation and task completion
US8538577B2 (en) * 2010-03-05 2013-09-17 Crown Equipment Limited Method and apparatus for sensing object load engagement, transportation and disengagement by automated vehicles
DE102010012187B4 (en) * 2010-03-19 2020-12-31 Sew-Eurodrive Gmbh & Co Kg Method for determining the position of at least a first and a second vehicle within an installation
US8602893B2 (en) * 2010-06-02 2013-12-10 Sony Computer Entertainment Inc. Input for computer device using pattern-based computer vision
US9229089B2 (en) 2010-06-10 2016-01-05 Qualcomm Incorporated Acquisition of navigation assistance information for a mobile station
US20120027251A1 (en) * 2010-07-30 2012-02-02 Wei Wu Device with markings for configuration
US9118832B2 (en) * 2010-08-17 2015-08-25 Nokia Technologies Oy Input method
US8793036B2 (en) * 2010-09-22 2014-07-29 The Boeing Company Trackless transit system with adaptive vehicles
GB2484316A (en) * 2010-10-06 2012-04-11 St Microelectronics Res & Dev Self navigation of mobile devices
US10127606B2 (en) 2010-10-13 2018-11-13 Ebay Inc. Augmented reality system and method for visualizing an item
US8561897B2 (en) 2010-11-18 2013-10-22 Sky-Trax, Inc. Load tracking utilizing load identifying indicia and spatial discrimination
US9341720B2 (en) * 2011-01-11 2016-05-17 Qualcomm Incorporated Camera-based position location and navigation based on image processing
EP2477000A1 (en) * 2011-01-14 2012-07-18 Leica Geosystems AG Measuring device with an automatic imaging swap function
US8862395B2 (en) * 2011-01-31 2014-10-14 Raytheon Company Coded marker navigation system and method
DE102011005439B4 (en) * 2011-03-11 2018-02-15 Siemens Healthcare Gmbh Medical device unit with an integrated positioning device
KR102041093B1 (en) 2011-04-11 2019-11-06 크라운 이큅먼트 코포레이션 Method and apparatus for efficient scheduling for multiple automated non-holonomic vehicles using a coordinated path planner
US8655588B2 (en) 2011-05-26 2014-02-18 Crown Equipment Limited Method and apparatus for providing accurate localization for an industrial vehicle
US9739616B2 (en) 2011-06-02 2017-08-22 Honda Motor Co., Ltd. Target recognition and localization methods using a laser sensor for wheeled mobile robots
US8548671B2 (en) 2011-06-06 2013-10-01 Crown Equipment Limited Method and apparatus for automatically calibrating vehicle parameters
US8594923B2 (en) 2011-06-14 2013-11-26 Crown Equipment Limited Method and apparatus for sharing map data associated with automated industrial vehicles
US8589012B2 (en) 2011-06-14 2013-11-19 Crown Equipment Limited Method and apparatus for facilitating map data processing for industrial vehicle navigation
WO2012172548A1 (en) * 2011-06-14 2012-12-20 Youval Nehmadi Method for translating a movement and an orientation of a predefined object into a computer generated data
US9101994B2 (en) 2011-08-10 2015-08-11 Illinois Tool Works Inc. System and device for welding training
US8844820B2 (en) 2011-08-24 2014-09-30 Hill-Rom Services, Inc. Multi-directional optical reader for a patient support
US20140058634A1 (en) 2012-08-24 2014-02-27 Crown Equipment Limited Method and apparatus for using unique landmarks to locate industrial vehicles at start-up
US20130054129A1 (en) * 2011-08-26 2013-02-28 INRO Technologies Limited Method and apparatus for using unique landmarks to locate industrial vehicles at start-up
US8757477B2 (en) * 2011-08-26 2014-06-24 Qualcomm Incorporated Identifier generation for visual beacon
US20140253737A1 (en) * 2011-09-07 2014-09-11 Yitzchak Kempinski System and method of tracking an object in an image captured by a moving device
US9056754B2 (en) 2011-09-07 2015-06-16 Crown Equipment Limited Method and apparatus for using pre-positioned objects to localize an industrial vehicle
US20130076346A1 (en) * 2011-09-23 2013-03-28 Caterpillar Inc. System and method of determining relative position
US9317037B2 (en) * 2011-10-03 2016-04-19 Vocollect, Inc. Warehouse vehicle navigation system and method
US9449342B2 (en) 2011-10-27 2016-09-20 Ebay Inc. System and method for visualization of items in an environment using augmented reality
JP5783885B2 (en) * 2011-11-11 2015-09-24 株式会社東芝 Information presentation apparatus, method and program thereof
CN102590841B (en) * 2011-12-20 2014-07-09 北京卫星环境工程研究所 Method for marking coordinate system in indoor or outdoor testing field and dynamic measuring method for lunar vehicle position and attitude
US9513127B2 (en) * 2011-12-22 2016-12-06 AppLabz, LLC Systems, methods, and apparatus for providing indoor navigation
US9702707B2 (en) 2011-12-22 2017-07-11 AppLabz, LLC Systems, methods, and apparatus for providing indoor navigation using optical floor sensors
US9243918B2 (en) 2011-12-22 2016-01-26 AppLabz, LLC Systems, methods, and apparatus for providing indoor navigation using magnetic sensors
US9240059B2 (en) 2011-12-29 2016-01-19 Ebay Inc. Personal augmented reality
US9573215B2 (en) 2012-02-10 2017-02-21 Illinois Tool Works Inc. Sound-based weld travel speed sensing system and method
DE102012101500A1 (en) 2012-02-24 2013-08-29 Dr. Schniz GmbH Method for detecting data describing charging, movement and local position states of forklift truck, involves detecting data describing charging state, movement state and local position of vehicle by module
DE102012208132A1 (en) * 2012-05-15 2013-11-21 Bayerische Motoren Werke Aktiengesellschaft Method for vehicle localization
US10846766B2 (en) 2012-06-29 2020-11-24 Ebay Inc. Contextual menus based on image recognition
US9728228B2 (en) 2012-08-10 2017-08-08 Smartdrive Systems, Inc. Vehicle event playback apparatus and methods
JP5992761B2 (en) * 2012-08-13 2016-09-14 日本電気通信システム株式会社 Vacuum cleaner, vacuum cleaner system, and control method of vacuum cleaner
DE102012214579A1 (en) * 2012-08-16 2014-02-20 Siemens Aktiengesellschaft Container plant and its operation
US9336541B2 (en) 2012-09-21 2016-05-10 Paypal, Inc. Augmented reality product instructions, tutorials and visualizations
JP5811980B2 (en) * 2012-09-25 2015-11-11 株式会社ダイフク Moving body posture discrimination system
JP5811981B2 (en) * 2012-09-25 2015-11-11 株式会社ダイフク Moving body posture discrimination system
US9368045B2 (en) 2012-11-09 2016-06-14 Illinois Tool Works Inc. System and device for welding training
US9583014B2 (en) 2012-11-09 2017-02-28 Illinois Tool Works Inc. System and device for welding training
EP2735844B1 (en) * 2012-11-26 2023-10-04 BlackBerry Limited System and method for indoor navigation
GB2511096A (en) * 2013-02-22 2014-08-27 Fox Murphy Ltd A Mobile Indoor Navigation System
US9583023B2 (en) 2013-03-15 2017-02-28 Illinois Tool Works Inc. Welding torch for a welding training system
US20140267703A1 (en) * 2013-03-15 2014-09-18 Robert M. Taylor Method and Apparatus of Mapping Landmark Position and Orientation
US9672757B2 (en) 2013-03-15 2017-06-06 Illinois Tool Works Inc. Multi-mode software and method for a welding training system
US9666100B2 (en) 2013-03-15 2017-05-30 Illinois Tool Works Inc. Calibration devices for a welding training system
WO2014152430A1 (en) * 2013-03-15 2014-09-25 Huntington Ingalls, Inc. Method and system for disambiguation of augmented reality tracking databases
US9728103B2 (en) 2013-03-15 2017-08-08 Illinois Tool Works Inc. Data storage and analysis for a welding training system
US9713852B2 (en) 2013-03-15 2017-07-25 Illinois Tool Works Inc. Welding training systems and devices
GB2514573B (en) * 2013-05-29 2018-05-02 Bae Systems Plc Structure navigation
US11090753B2 (en) 2013-06-21 2021-08-17 Illinois Tool Works Inc. System and method for determining weld travel speed
US20150036016A1 (en) * 2013-07-30 2015-02-05 Qualcomm Incorporated Methods and apparatus for determining the orientation of a mobile phone in an indoor environment
US9880560B2 (en) * 2013-09-16 2018-01-30 Deere & Company Vehicle auto-motion control system
EP3056854B1 (en) * 2013-09-30 2020-10-14 National Institute of Advanced Industrial Science and Technology Marker image processing system
US9501878B2 (en) 2013-10-16 2016-11-22 Smartdrive Systems, Inc. Vehicle event playback apparatus and methods
US20160263763A1 (en) * 2013-10-22 2016-09-15 Mikkelsen Converting Technologies, Inc. Vision system
US20150130936A1 (en) * 2013-11-08 2015-05-14 Dow Agrosciences Llc Crop monitoring system
US9610955B2 (en) 2013-11-11 2017-04-04 Smartdrive Systems, Inc. Vehicle fuel consumption monitor and feedback systems
US9233468B2 (en) * 2013-11-12 2016-01-12 Irobot Corporation Commanding a mobile robot using glyphs
KR101533824B1 (en) * 2013-11-12 2015-07-03 (주) 씨티아이마이크로 System and Method for Preventing Animals from Approaching Certain Area Using Image Recognition
WO2015072188A1 (en) 2013-11-15 2015-05-21 株式会社Ihi Inspection system
US10056010B2 (en) 2013-12-03 2018-08-21 Illinois Tool Works Inc. Systems and methods for a weld training system
CN104748754B (en) * 2013-12-31 2017-11-10 财团法人车辆研究测试中心 Vehicle positioning method and its system
US9207677B2 (en) * 2014-01-02 2015-12-08 Automotive Research & Testing Center Vehicle positioning method and its system
US10105782B2 (en) 2014-01-07 2018-10-23 Illinois Tool Works Inc. Feedback from a welding torch of a welding system
US9751149B2 (en) 2014-01-07 2017-09-05 Illinois Tool Works Inc. Welding stand for a welding system
US9589481B2 (en) 2014-01-07 2017-03-07 Illinois Tool Works Inc. Welding software for detection and control of devices and for analysis of data
US10170019B2 (en) 2014-01-07 2019-01-01 Illinois Tool Works Inc. Feedback from a welding torch of a welding system
US9757819B2 (en) 2014-01-07 2017-09-12 Illinois Tool Works Inc. Calibration tool and method for a welding system
US9724788B2 (en) 2014-01-07 2017-08-08 Illinois Tool Works Inc. Electrical assemblies for a welding system
US9138895B2 (en) 2014-01-10 2015-09-22 Recognition Robotics, Inc. Method for picking up an article using a robot arm and associated system
DE102014000375A1 (en) 2014-01-14 2015-07-16 Grenzebach Maschinenbau Gmbh Device for orientation for automatically in factory halls run, electrically operated, transport vehicles
US8892310B1 (en) 2014-02-21 2014-11-18 Smartdrive Systems, Inc. System and method to detect execution of driving maneuvers
US10310054B2 (en) * 2014-03-21 2019-06-04 The Boeing Company Relative object localization process for local positioning system
WO2015160828A1 (en) 2014-04-15 2015-10-22 Huntington Ingalls Incorporated System and method for augmented reality display of dynamic environment information
US9937578B2 (en) 2014-06-27 2018-04-10 Illinois Tool Works Inc. System and method for remote welding training
US9862049B2 (en) 2014-06-27 2018-01-09 Illinois Tool Works Inc. System and method of welding system operator identification
US10665128B2 (en) 2014-06-27 2020-05-26 Illinois Tool Works Inc. System and method of monitoring welding information
US10307853B2 (en) 2014-06-27 2019-06-04 Illinois Tool Works Inc. System and method for managing welding data
EP2977842A1 (en) * 2014-07-23 2016-01-27 F. Hoffmann-La Roche AG Laboratory sample distribution system and laboratory automation system
US11014183B2 (en) 2014-08-07 2021-05-25 Illinois Tool Works Inc. System and method of marking a welding workpiece
US9724787B2 (en) 2014-08-07 2017-08-08 Illinois Tool Works Inc. System and method of monitoring a welding environment
US9875665B2 (en) 2014-08-18 2018-01-23 Illinois Tool Works Inc. Weld training system and method
US9927797B2 (en) * 2014-08-29 2018-03-27 Amazon Technologies, Inc. Safety compliance for mobile drive units
DE102014219798A1 (en) * 2014-09-30 2016-03-31 Siemens Aktiengesellschaft Mobile terminal and orientation determination method on a mobile terminal
US10239147B2 (en) 2014-10-16 2019-03-26 Illinois Tool Works Inc. Sensor-based power controls for a welding system
US11247289B2 (en) 2014-10-16 2022-02-15 Illinois Tool Works Inc. Remote power supply parameter adjustment
US9706105B2 (en) 2014-10-20 2017-07-11 Symbol Technologies, Llc Apparatus and method for specifying and aiming cameras at shelves
CN106687878B (en) * 2014-10-31 2021-01-22 深圳市大疆创新科技有限公司 System and method for monitoring with visual indicia
US10417934B2 (en) 2014-11-05 2019-09-17 Illinois Tool Works Inc. System and method of reviewing weld data
US10490098B2 (en) 2014-11-05 2019-11-26 Illinois Tool Works Inc. System and method of recording multi-run data
US10210773B2 (en) 2014-11-05 2019-02-19 Illinois Tool Works Inc. System and method for welding torch display
US10204406B2 (en) 2014-11-05 2019-02-12 Illinois Tool Works Inc. System and method of controlling welding system camera exposure and marker illumination
US10402959B2 (en) 2014-11-05 2019-09-03 Illinois Tool Works Inc. System and method of active torch marker control
US10373304B2 (en) 2014-11-05 2019-08-06 Illinois Tool Works Inc. System and method of arranging welding device markers
US11069257B2 (en) 2014-11-13 2021-07-20 Smartdrive Systems, Inc. System and method for detecting a vehicle event and generating review criteria
DE102014224082A1 (en) * 2014-11-26 2016-06-02 Robert Bosch Gmbh A method of operating a vehicle and operating a manufacturing system
DE102014018082C5 (en) * 2014-12-08 2024-08-29 Bomag Gmbh Method for controlling a construction machine, control system for a construction machine, and construction machine
US9541409B2 (en) 2014-12-18 2017-01-10 Nissan North America, Inc. Marker aided autonomous vehicle localization
US9448559B2 (en) 2015-01-15 2016-09-20 Nissan North America, Inc. Autonomous vehicle routing and navigation using passenger docking locations
US9625906B2 (en) 2015-01-15 2017-04-18 Nissan North America, Inc. Passenger docking location selection
US9519290B2 (en) 2015-01-15 2016-12-13 Nissan North America, Inc. Associating passenger docking locations with destinations
US9436183B2 (en) 2015-01-15 2016-09-06 Nissan North America, Inc. Associating passenger docking locations with destinations using vehicle transportation network partitioning
EP3048557B1 (en) * 2015-01-20 2019-09-25 Aptiv Technologies Limited Method for determining a position of a vehicle characteristic
DE102015101381A1 (en) 2015-01-30 2016-08-04 Hubtex Maschinenbau Gmbh & Co. Kg Steering method, industrial truck and route guidance system
US9568335B2 (en) 2015-01-30 2017-02-14 Nissan North America, Inc. Associating parking areas with destinations based on automatically identified associations between vehicle operating information and non-vehicle operating information
US9151628B1 (en) 2015-01-30 2015-10-06 Nissan North America, Inc. Associating parking areas with destinations
US9697730B2 (en) 2015-01-30 2017-07-04 Nissan North America, Inc. Spatial clustering of vehicle probe data
US10223589B2 (en) 2015-03-03 2019-03-05 Cognex Corporation Vision system for training an assembly system through virtual assembly of objects
US9778658B2 (en) 2015-03-13 2017-10-03 Nissan North America, Inc. Pattern detection using probe data
US10120381B2 (en) 2015-03-13 2018-11-06 Nissan North America, Inc. Identifying significant locations based on vehicle probe data
US9679420B2 (en) * 2015-04-01 2017-06-13 Smartdrive Systems, Inc. Vehicle event recording system and method
US10427239B2 (en) 2015-04-02 2019-10-01 Illinois Tool Works Inc. Systems and methods for tracking weld training arc parameters
US9924103B2 (en) * 2015-04-09 2018-03-20 The Boeing Company Automated local positioning system calibration using optically readable markers
EP3104118B1 (en) * 2015-06-12 2019-02-27 Hexagon Technology Center GmbH Method to control a drive mechanism of an automated machine having a camera
US9758305B2 (en) 2015-07-31 2017-09-12 Locus Robotics Corp. Robotic navigation utilizing semantic mapping
US10373517B2 (en) 2015-08-12 2019-08-06 Illinois Tool Works Inc. Simulation stick welding electrode holder systems and methods
US10657839B2 (en) 2015-08-12 2020-05-19 Illinois Tool Works Inc. Stick welding electrode holders with real-time feedback features
US10438505B2 (en) 2015-08-12 2019-10-08 Illinois Tool Works Welding training system interface
US10593230B2 (en) 2015-08-12 2020-03-17 Illinois Tool Works Inc. Stick welding electrode holder systems and methods
FI20155599A (en) * 2015-08-21 2017-02-22 Konecranes Global Oy Control of a lifting device
US9382068B1 (en) 2015-09-29 2016-07-05 Amazon Technologies, Inc. Proximity directed stowage
CA3002911A1 (en) * 2015-10-22 2017-04-27 Grey Orange Pte Ltd Automated fault diagnosis and recovery of machines
US10940997B2 (en) * 2015-10-23 2021-03-09 Sato Holdings Kabushiki Kaisha Movement path management system, movement path management method, and non-transitory computer-readable medium
US20170124367A1 (en) * 2015-10-29 2017-05-04 Empire Technology Development Llc Alignment markers to facilitate detection of object orientation and deformation
CN105404842B (en) * 2015-11-19 2017-12-05 北京特种机械研究所 AGV positioning and directings and speed-measuring method based on terrestrial reference Quick Response Code
WO2017096360A1 (en) * 2015-12-03 2017-06-08 Osram Sylvania Inc. Light-based vehicle positioning for mobile transport systems
US10352689B2 (en) 2016-01-28 2019-07-16 Symbol Technologies, Llc Methods and systems for high precision locationing with depth values
US10503890B2 (en) * 2016-02-16 2019-12-10 Arizona Board Of Regents On Behalf Of Northern Arizona University Authentication of images extracted from unclonable objects
DE102016108446A1 (en) * 2016-05-06 2017-11-09 Terex Mhps Gmbh System and method for determining the position of a transport vehicle and transport vehicle
CN106002917A (en) * 2016-06-13 2016-10-12 刘哲 Electric pole type automatic warehousing robot
FR3052875B1 (en) * 2016-06-21 2018-07-13 Thales "HEAD HIGH" VISUALIZATION SYSTEM FOR AIRCRAFT HAVING A NON-CONTACT READING DEVICE FOR HARMONIZING PARAMETERS WITH THE AIRCRAFT
JP6760786B2 (en) * 2016-07-21 2020-09-23 Thk株式会社 Mobile robot and control method
JP6717121B2 (en) * 2016-08-29 2020-07-01 株式会社ダイフク Goods transport facility
EP3507666A1 (en) 2016-08-31 2019-07-10 Sew-Eurodrive GmbH & Co. KG System for sensing position and method for sensing position
JP2018036937A (en) * 2016-09-01 2018-03-08 住友電気工業株式会社 Image processing device, image processing system, image processing program and label
CN106526580A (en) * 2016-10-26 2017-03-22 哈工大机器人集团上海有限公司 Road sign, apparatus, and method for determining robot position
US11042161B2 (en) 2016-11-16 2021-06-22 Symbol Technologies, Llc Navigation control method and apparatus in a mobile automation system
WO2018115930A1 (en) * 2016-12-21 2018-06-28 Auto Drive Solutions S.L. System for guiding and positioning vehicles at low speed by means of optical systems
DE102016015499A1 (en) 2016-12-23 2018-06-28 Bomag Gmbh Ground milling machine, in particular road milling machine, and method for operating a ground milling machine
WO2018135063A1 (en) * 2017-01-17 2018-07-26 国立研究開発法人産業技術総合研究所 Marker, and posture estimation method and position and posture estimation method using marker
US9864890B1 (en) * 2017-01-25 2018-01-09 General Electric Company Systems and methods for contextualizing data obtained from barcode images
CN118195491A (en) 2017-02-13 2024-06-14 实耐宝公司 Automated tool data generation in an automated asset management system
US11449059B2 (en) 2017-05-01 2022-09-20 Symbol Technologies, Llc Obstacle detection for a mobile automation apparatus
US10726273B2 (en) 2017-05-01 2020-07-28 Symbol Technologies, Llc Method and apparatus for shelf feature and object placement detection from shelf images
US11367092B2 (en) 2017-05-01 2022-06-21 Symbol Technologies, Llc Method and apparatus for extracting and processing price text from an image set
US10663590B2 (en) 2017-05-01 2020-05-26 Symbol Technologies, Llc Device and method for merging lidar data
US10591918B2 (en) 2017-05-01 2020-03-17 Symbol Technologies, Llc Fixed segmented lattice planning for a mobile automation apparatus
US10505057B2 (en) 2017-05-01 2019-12-10 Symbol Technologies, Llc Device and method for operating cameras and light sources wherein parasitic reflections from a paired light source are not reflected into the paired camera
WO2018204308A1 (en) 2017-05-01 2018-11-08 Symbol Technologies, Llc Method and apparatus for object status detection
US10949798B2 (en) 2017-05-01 2021-03-16 Symbol Technologies, Llc Multimodal localization and mapping for a mobile automation apparatus
US11093896B2 (en) 2017-05-01 2021-08-17 Symbol Technologies, Llc Product status detection system
WO2018201423A1 (en) 2017-05-05 2018-11-08 Symbol Technologies, Llc Method and apparatus for detecting and interpreting price label text
DE102018002947A1 (en) * 2017-05-10 2018-11-15 Sew-Eurodrive Gmbh & Co Kg Method for determining the position of a mobile part and information carrier for carrying out a method
US10275663B2 (en) * 2017-05-11 2019-04-30 Passion Mobility Ltd. Indoor navigation method and system
EP3421936A1 (en) * 2017-06-30 2019-01-02 Panasonic Automotive & Industrial Systems Europe GmbH Optical marker element for geo location information
WO2019006651A1 (en) * 2017-07-04 2019-01-10 王勇 Space positioning method and system
JP6998514B2 (en) * 2017-07-11 2022-01-18 パナソニックIpマネジメント株式会社 Robot control device
DE102018116065A1 (en) 2017-07-13 2019-01-17 Vorwerk & Co. Interholding Gmbh Method for operating a self-propelled service device
DE102017115847A1 (en) * 2017-07-14 2019-01-17 Vorwerk & Co. Interholding Gmbh Method for operating a self-propelled robot
CN109282814B (en) 2017-07-21 2023-08-29 中兴通讯股份有限公司 Positioning method, device and system, positioning system layout method and storage medium
CN107727104B (en) * 2017-08-16 2019-04-30 北京极智嘉科技有限公司 Positioning and map building air navigation aid, apparatus and system while in conjunction with mark
US10521914B2 (en) 2017-09-07 2019-12-31 Symbol Technologies, Llc Multi-sensor object recognition system and method
US10572763B2 (en) 2017-09-07 2020-02-25 Symbol Technologies, Llc Method and apparatus for support surface edge detection
CN107678432A (en) * 2017-10-16 2018-02-09 上海斐讯数据通信技术有限公司 Control method and automatic carriage, the system of a kind of automatic carriage
US20190128994A1 (en) * 2017-10-31 2019-05-02 Richard Kozdras Sensor system
JP6701153B2 (en) * 2017-11-10 2020-05-27 株式会社Subaru Position measurement system for moving objects
CN107678440A (en) * 2017-11-16 2018-02-09 苏州艾吉威机器人有限公司 A kind of complementary locating formations, include its self-discipline mobile device and localization method
WO2019100011A1 (en) 2017-11-17 2019-05-23 Divine Logic, Inc. Systems and methods for tracking items
US10692289B2 (en) * 2017-11-22 2020-06-23 Google Llc Positional recognition for augmented reality environment
CN109552416A (en) * 2017-12-19 2019-04-02 李超 Learner-driven vehicle
CN109978110B (en) * 2017-12-28 2022-01-28 沈阳新松机器人自动化股份有限公司 Two-dimensional code for AGV positioning and navigation and decoding method
GB201800751D0 (en) * 2018-01-17 2018-02-28 Mo Sys Engineering Ltd Bulk Handling
JP2019132805A (en) * 2018-02-02 2019-08-08 株式会社エンプラス Marker
US10935374B2 (en) * 2018-02-21 2021-03-02 Faro Technologies, Inc. Systems and methods for generating models of scanned environments
US10838425B2 (en) * 2018-02-21 2020-11-17 Waymo Llc Determining and responding to an internal status of a vehicle
WO2019173585A2 (en) * 2018-03-08 2019-09-12 Global Traffic Technologies, Llc Determining position of vehicle based on image of tag
US10832436B2 (en) 2018-04-05 2020-11-10 Symbol Technologies, Llc Method, system and apparatus for recovering label positions
US10823572B2 (en) 2018-04-05 2020-11-03 Symbol Technologies, Llc Method, system and apparatus for generating navigational data
US10809078B2 (en) 2018-04-05 2020-10-20 Symbol Technologies, Llc Method, system and apparatus for dynamic path generation
US10740911B2 (en) 2018-04-05 2020-08-11 Symbol Technologies, Llc Method, system and apparatus for correcting translucency artifacts in data representing a support structure
US11327504B2 (en) 2018-04-05 2022-05-10 Symbol Technologies, Llc Method, system and apparatus for mobile automation apparatus localization
JP7116358B2 (en) * 2018-04-27 2022-08-10 ブラザー工業株式会社 Image processing device and computer program
EP3799661B1 (en) 2018-05-11 2024-01-10 Precision Point Systems, LLC Method for absolute positioning of an object
DE102018113840A1 (en) * 2018-06-11 2019-12-12 Osram Gmbh LABELING AND SYSTEM FOR POSITIONING AND / OR ENVIRONMENTAL DETERMINATION AND DEVICE AND METHOD FOR DETERMINING POSITION AND / OR FOR DISPLAYING AR-CONTENT
US10643065B2 (en) 2018-06-21 2020-05-05 Atlassian Pty Ltd Techniques for document creation based on image sections
CN109093621B (en) * 2018-08-10 2021-03-12 北京极智嘉科技有限公司 Robot operation precision monitoring method and device, robot, server and medium
US11745354B2 (en) 2018-08-16 2023-09-05 Mitutoyo Corporation Supplementary metrology position coordinates determination system including an alignment sensor for use with a robot
US10751883B2 (en) 2018-08-16 2020-08-25 Mitutoyo Corporation Robot system with supplementary metrology position coordinates determination system
US11002529B2 (en) 2018-08-16 2021-05-11 Mitutoyo Corporation Robot system with supplementary metrology position determination system
US10871366B2 (en) 2018-08-16 2020-12-22 Mitutoyo Corporation Supplementary metrology position coordinates determination system for use with a robot
US10913156B2 (en) 2018-09-24 2021-02-09 Mitutoyo Corporation Robot system with end tool metrology position coordinates determination system
EP3629221A1 (en) * 2018-09-27 2020-04-01 Siemens Aktiengesellschaft Landmark tape and landmark dispenser
US11604476B1 (en) * 2018-10-05 2023-03-14 Glydways Inc. Road-based vehicle guidance system
US11506483B2 (en) 2018-10-05 2022-11-22 Zebra Technologies Corporation Method, system and apparatus for support structure depth determination
US11010920B2 (en) 2018-10-05 2021-05-18 Zebra Technologies Corporation Method, system and apparatus for object detection in point clouds
FR3087568A1 (en) * 2018-10-23 2020-04-24 Psa Automobiles Sa METHOD FOR LOCATING A VEHICLE IN A STRUCTURE
SG11202104325UA (en) * 2018-10-30 2021-05-28 Alt Llc System and method for the reverese optical tracking of a moving object
US11090811B2 (en) 2018-11-13 2021-08-17 Zebra Technologies Corporation Method and apparatus for labeling of support structures
US11003188B2 (en) 2018-11-13 2021-05-11 Zebra Technologies Corporation Method, system and apparatus for obstacle handling in navigational path generation
KR102162756B1 (en) * 2018-11-16 2020-10-07 주식회사 로탈 Mobile robot platform system for process and production management
US10728536B2 (en) * 2018-11-21 2020-07-28 Ubicquia Iq Llc System and method for camera commissioning beacons
DE102018221142A1 (en) * 2018-12-06 2020-06-10 Robert Bosch Gmbh Localization in complex traffic scenarios using markings
US11079240B2 (en) 2018-12-07 2021-08-03 Zebra Technologies Corporation Method, system and apparatus for adaptive particle filter localization
US11416000B2 (en) 2018-12-07 2022-08-16 Zebra Technologies Corporation Method and apparatus for navigational ray tracing
US11100303B2 (en) 2018-12-10 2021-08-24 Zebra Technologies Corporation Method, system and apparatus for auxiliary label detection and association
US11015938B2 (en) 2018-12-12 2021-05-25 Zebra Technologies Corporation Method, system and apparatus for navigational assistance
US10731970B2 (en) 2018-12-13 2020-08-04 Zebra Technologies Corporation Method, system and apparatus for support structure detection
CN109612477A (en) * 2018-12-18 2019-04-12 盐城工学院 A kind of mobile robot autonomous navigation method of integrated application artificial landmark and grating map
US12080027B2 (en) * 2018-12-27 2024-09-03 Nec Communication Systems, Ltd. Article position managing apparatus, article position management system, article position managing method, and program
JP7336752B2 (en) * 2018-12-28 2023-09-01 パナソニックIpマネジメント株式会社 Positioning device and moving object
CA3028708A1 (en) 2018-12-28 2020-06-28 Zih Corp. Method, system and apparatus for dynamic loop closure in mapping trajectories
JP7336753B2 (en) * 2018-12-28 2023-09-01 パナソニックIpマネジメント株式会社 Positioning device and moving body
US11810473B2 (en) 2019-01-29 2023-11-07 The Regents Of The University Of California Optical surface tracking for medical simulation
US11495142B2 (en) 2019-01-30 2022-11-08 The Regents Of The University Of California Ultrasound trainer with internal optical tracking
US11221631B2 (en) 2019-04-24 2022-01-11 Innovation First, Inc. Performance arena for robots with position location system
US11151792B2 (en) 2019-04-26 2021-10-19 Google Llc System and method for creating persistent mappings in augmented reality
US11163997B2 (en) 2019-05-05 2021-11-02 Google Llc Methods and apparatus for venue based augmented reality
CN111950314A (en) * 2019-05-17 2020-11-17 锥能机器人(上海)有限公司 Positioning method and device, machine readable medium and system thereof
US11341663B2 (en) 2019-06-03 2022-05-24 Zebra Technologies Corporation Method, system and apparatus for detecting support structure obstructions
US11151743B2 (en) 2019-06-03 2021-10-19 Zebra Technologies Corporation Method, system and apparatus for end of aisle detection
US11080566B2 (en) 2019-06-03 2021-08-03 Zebra Technologies Corporation Method, system and apparatus for gap detection in support structures with peg regions
US11200677B2 (en) 2019-06-03 2021-12-14 Zebra Technologies Corporation Method, system and apparatus for shelf edge detection
US11960286B2 (en) 2019-06-03 2024-04-16 Zebra Technologies Corporation Method, system and apparatus for dynamic task sequencing
US11662739B2 (en) 2019-06-03 2023-05-30 Zebra Technologies Corporation Method, system and apparatus for adaptive ceiling-based localization
US11402846B2 (en) 2019-06-03 2022-08-02 Zebra Technologies Corporation Method, system and apparatus for mitigating data capture light leakage
US11034092B2 (en) * 2019-06-17 2021-06-15 International Business Machines Corporation 3D-printed object with dynamic augmented-reality textures
US11776423B2 (en) 2019-07-22 2023-10-03 Illinois Tool Works Inc. Connection boxes for gas tungsten arc welding training systems
US11288978B2 (en) 2019-07-22 2022-03-29 Illinois Tool Works Inc. Gas tungsten arc welding training systems
WO2021091989A1 (en) * 2019-11-05 2021-05-14 Continental Automotive Systems, Inc. System and method for precise vehicle positioning using bar codes, polygons and projective transformation
US11507103B2 (en) 2019-12-04 2022-11-22 Zebra Technologies Corporation Method, system and apparatus for localization-based historical obstacle handling
US11107238B2 (en) 2019-12-13 2021-08-31 Zebra Technologies Corporation Method, system and apparatus for detecting item facings
WO2021154111A1 (en) * 2020-01-28 2021-08-05 Limited Liability Company "Topcon Positioning Systems" System and method for controlling an implement on a work machine using machine vision
US11733700B2 (en) * 2020-02-12 2023-08-22 Crown Equipment Corporation Automating control of an industrial vehicle
US11822333B2 (en) 2020-03-30 2023-11-21 Zebra Technologies Corporation Method, system and apparatus for data capture illumination control
EP4158463A4 (en) * 2020-05-27 2024-06-12 Vimaan Robotics, Inc. Real time event tracking and digitization for warehouse inventory management
US11022444B1 (en) 2020-06-16 2021-06-01 Geotab Inc. Dataset simplification of multidimensional signals captured for asset tracking
US11450024B2 (en) 2020-07-17 2022-09-20 Zebra Technologies Corporation Mixed depth object detection
JP6860735B1 (en) * 2020-07-28 2021-04-21 Dmg森精機株式会社 Transport system, transport system control method, and transport system control program
US11593329B2 (en) 2020-07-31 2023-02-28 Geotab Inc. Methods and devices for fixed extrapolation error data simplification processes for telematics
US11556509B1 (en) 2020-07-31 2023-01-17 Geotab Inc. Methods and devices for fixed interpolation error data simplification processes for telematic
US11609888B2 (en) 2020-07-31 2023-03-21 Geotab Inc. Methods and systems for fixed interpolation error data simplification processes for telematics
FR3113943B1 (en) * 2020-09-09 2022-08-19 Commissariat Energie Atomique A method of determining the position and orientation of a vehicle.
EP3974936B1 (en) * 2020-09-25 2023-06-07 Sick Ag Configuration of a visualisation device for a machine area
GB2599159A (en) * 2020-09-28 2022-03-30 Mastercard International Inc Location determination
US11593915B2 (en) 2020-10-21 2023-02-28 Zebra Technologies Corporation Parallax-tolerant panoramic image generation
US11392891B2 (en) 2020-11-03 2022-07-19 Zebra Technologies Corporation Item placement detection and optimization in material handling systems
CN112091980B (en) * 2020-11-10 2021-03-05 杭州迦智科技有限公司 Method, device and storage medium for positioning consistency of at least two positioning objects
US11847832B2 (en) 2020-11-11 2023-12-19 Zebra Technologies Corporation Object classification for autonomous navigation systems
US11546395B2 (en) 2020-11-24 2023-01-03 Geotab Inc. Extrema-retentive data buffering and simplification
US11838364B2 (en) 2020-11-24 2023-12-05 Geotab Inc. Extrema-retentive data buffering and simplification
CN112767487B (en) * 2021-01-27 2024-04-05 京东科技信息技术有限公司 Positioning method, device and system of robot
US11954882B2 (en) 2021-06-17 2024-04-09 Zebra Technologies Corporation Feature-based georegistration for mobile computing devices
DE102021206987B4 (en) 2021-07-02 2024-06-27 Pepperl+Fuchs Se Device for presenting a code and method for detecting the sequence of carriers of such devices along a code path
CN113683018A (en) * 2021-08-23 2021-11-23 北京京东乾石科技有限公司 Shelf displacement deviation correction method and device, automatic guided vehicle and storage medium
DE102022111110A1 (en) 2022-05-05 2023-11-09 Bayerische Motoren Werke Aktiengesellschaft Marker device for position determination and method for installing a marker device
IT202200009620A1 (en) * 2022-05-10 2023-11-10 Fiat Ricerche "Motor vehicle driving assistance system and corresponding procedure"
JP7299442B1 (en) * 2022-11-17 2023-06-27 ファナック株式会社 Control device, three-dimensional position measurement system, and program

Citations (29)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4684247A (en) 1985-10-18 1987-08-04 Calspan Corporation Target member for use in a positioning system
EP0367526A2 (en) 1988-10-31 1990-05-09 Texas Instruments Incorporated Closed-loop navigation system for mobile robots
US5051906A (en) 1989-06-07 1991-09-24 Transitions Research Corporation Mobile robot navigation employing retroreflective ceiling features
US5367458A (en) 1993-08-10 1994-11-22 Caterpillar Industrial Inc. Apparatus and method for identifying scanned reflective anonymous targets
US5525883A (en) 1994-07-08 1996-06-11 Sara Avitzour Mobile robot location determination employing error-correcting distributed landmarks
US5604715A (en) 1994-06-21 1997-02-18 Aman; James A. Automated lumber unit trucking system
US5617335A (en) 1992-01-30 1997-04-01 Fujitsu Limited System for and method of recognizating and tracking target mark
US5793934A (en) 1994-06-22 1998-08-11 Siemens Aktiengesellschaft Method for the orientation, route planning and control of an autonomous mobile unit
US5828770A (en) 1996-02-20 1998-10-27 Northern Digital Inc. System for determining the spatial position and angular orientation of an object
US5832139A (en) 1996-07-31 1998-11-03 Omniplanar, Inc. Method and apparatus for determining degrees of freedom of a camera
US5893043A (en) 1995-08-30 1999-04-06 Daimler-Benz Ag Process and arrangement for determining the position of at least one point of a track-guided vehicle
US6137893A (en) 1996-10-07 2000-10-24 Cognex Corporation Machine vision calibration targets and methods of determining their location and orientation in an image
US6453223B1 (en) 1996-11-05 2002-09-17 Carnegie Mellon University Infrastructure independent position determining system
US6542824B1 (en) 1999-01-29 2003-04-01 International Business Machines Corporation Method and system for determining position information utilizing a portable electronic device lacking global positioning system (GPS) reception capability
US6556722B1 (en) 1997-05-30 2003-04-29 British Broadcasting Corporation Position determination
US6661449B1 (en) 1996-06-06 2003-12-09 Fuji Jukogyo Kabushiki Kaisha Object recognizing apparatus for vehicle and the method thereof
US20040016077A1 (en) * 2002-07-26 2004-01-29 Samsung Gwangju Electronics Co., Ltd. Robot cleaner, robot cleaning system and method of controlling same
US6697761B2 (en) 2000-09-19 2004-02-24 Olympus Optical Co., Ltd. Three-dimensional position/orientation sensing apparatus, information presenting system, and model error detecting system
US6728582B1 (en) 2000-12-15 2004-04-27 Cognex Corporation System and method for determining the position of an object in three dimensions using a machine vision system with two cameras
US6732045B1 (en) 1999-08-13 2004-05-04 Locanis Technologies Gmbh Method and device for detecting the position of a vehicle in a given area
EP1437636A1 (en) 2003-01-11 2004-07-14 Samsung Electronics Co., Ltd. Mobile robot, and system and method for autonomous navigation of the same
US20040183751A1 (en) * 2001-10-19 2004-09-23 Dempski Kelly L Industrial augmented reality
US6859729B2 (en) 2002-10-21 2005-02-22 Bae Systems Integrated Defense Solutions Inc. Navigation of remote controlled vehicles
US7370803B2 (en) 2004-08-13 2008-05-13 Dofasco Inc. Remote crane bar code system
US7667646B2 (en) 2006-02-21 2010-02-23 Nokia Corporation System and methods for direction finding using a handheld device
US7681796B2 (en) * 2006-01-05 2010-03-23 International Business Machines Corporation Mobile device tracking
US20100091096A1 (en) * 2008-10-10 2010-04-15 Canon Kabushiki Kaisha Image processing apparatus and image processing method
US7721967B2 (en) 2004-08-13 2010-05-25 Arcelormittal Dofasco Inc. Remote crane bar code system
US7845560B2 (en) * 2004-12-14 2010-12-07 Sky-Trax Incorporated Method and apparatus for determining position and rotational orientation of an object

Patent Citations (30)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4684247A (en) 1985-10-18 1987-08-04 Calspan Corporation Target member for use in a positioning system
EP0367526A2 (en) 1988-10-31 1990-05-09 Texas Instruments Incorporated Closed-loop navigation system for mobile robots
US5051906A (en) 1989-06-07 1991-09-24 Transitions Research Corporation Mobile robot navigation employing retroreflective ceiling features
US5617335A (en) 1992-01-30 1997-04-01 Fujitsu Limited System for and method of recognizating and tracking target mark
US5367458A (en) 1993-08-10 1994-11-22 Caterpillar Industrial Inc. Apparatus and method for identifying scanned reflective anonymous targets
US5604715A (en) 1994-06-21 1997-02-18 Aman; James A. Automated lumber unit trucking system
US5793934A (en) 1994-06-22 1998-08-11 Siemens Aktiengesellschaft Method for the orientation, route planning and control of an autonomous mobile unit
US5525883A (en) 1994-07-08 1996-06-11 Sara Avitzour Mobile robot location determination employing error-correcting distributed landmarks
US5893043A (en) 1995-08-30 1999-04-06 Daimler-Benz Ag Process and arrangement for determining the position of at least one point of a track-guided vehicle
US5828770A (en) 1996-02-20 1998-10-27 Northern Digital Inc. System for determining the spatial position and angular orientation of an object
US6661449B1 (en) 1996-06-06 2003-12-09 Fuji Jukogyo Kabushiki Kaisha Object recognizing apparatus for vehicle and the method thereof
US5832139A (en) 1996-07-31 1998-11-03 Omniplanar, Inc. Method and apparatus for determining degrees of freedom of a camera
US6137893A (en) 1996-10-07 2000-10-24 Cognex Corporation Machine vision calibration targets and methods of determining their location and orientation in an image
US6453223B1 (en) 1996-11-05 2002-09-17 Carnegie Mellon University Infrastructure independent position determining system
US6556722B1 (en) 1997-05-30 2003-04-29 British Broadcasting Corporation Position determination
US6542824B1 (en) 1999-01-29 2003-04-01 International Business Machines Corporation Method and system for determining position information utilizing a portable electronic device lacking global positioning system (GPS) reception capability
US6732045B1 (en) 1999-08-13 2004-05-04 Locanis Technologies Gmbh Method and device for detecting the position of a vehicle in a given area
US6697761B2 (en) 2000-09-19 2004-02-24 Olympus Optical Co., Ltd. Three-dimensional position/orientation sensing apparatus, information presenting system, and model error detecting system
US6728582B1 (en) 2000-12-15 2004-04-27 Cognex Corporation System and method for determining the position of an object in three dimensions using a machine vision system with two cameras
US20040183751A1 (en) * 2001-10-19 2004-09-23 Dempski Kelly L Industrial augmented reality
US7372451B2 (en) 2001-10-19 2008-05-13 Accenture Global Services Gmbh Industrial augmented reality
US20040016077A1 (en) * 2002-07-26 2004-01-29 Samsung Gwangju Electronics Co., Ltd. Robot cleaner, robot cleaning system and method of controlling same
US6859729B2 (en) 2002-10-21 2005-02-22 Bae Systems Integrated Defense Solutions Inc. Navigation of remote controlled vehicles
EP1437636A1 (en) 2003-01-11 2004-07-14 Samsung Electronics Co., Ltd. Mobile robot, and system and method for autonomous navigation of the same
US7370803B2 (en) 2004-08-13 2008-05-13 Dofasco Inc. Remote crane bar code system
US7721967B2 (en) 2004-08-13 2010-05-25 Arcelormittal Dofasco Inc. Remote crane bar code system
US7845560B2 (en) * 2004-12-14 2010-12-07 Sky-Trax Incorporated Method and apparatus for determining position and rotational orientation of an object
US7681796B2 (en) * 2006-01-05 2010-03-23 International Business Machines Corporation Mobile device tracking
US7667646B2 (en) 2006-02-21 2010-02-23 Nokia Corporation System and methods for direction finding using a handheld device
US20100091096A1 (en) * 2008-10-10 2010-04-15 Canon Kabushiki Kaisha Image processing apparatus and image processing method

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
C. B. Owen et al., "What is the best fiducial?," in Augmented Reality Toolkit, the First IEEE International Workshop, 2002.
M. Fiala, "Vision guided control of multiple robots," in Proceedings of the First Canadian Conference on Computer and Robot Vision, (Washington DC, USA), IEEE Computer Society, May 2004, pp. 241-246.
R. Baczyk et al., "Vision-Based Mobile Robot Localization With Simple Artificial Landmarks," Prep. 7th IFAC Symp. Robot Control, Wroclaw, Poland, 2003, pp. 217-222.
S. Aoyagi et al., "A Position and Orientation Measurement of a Mobile Robot by Image Recognition of Simple Barcode Landmarks and Compensation of Inclinations," Trans. The Institute of Electrical Engineers of Japan, 121-C, 2, 2001.
Third Party Observations dated Oct. 13, 2011 filed in related European Patent Application No. 05848492.4.

Cited By (49)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10511926B2 (en) 2007-10-17 2019-12-17 Symbol Technologies, Llc Self-localization and self-orientation of a ceiling-mounted device
US9165467B2 (en) * 2012-08-06 2015-10-20 Cloudparc, Inc. Defining a handoff zone for tracking a vehicle between cameras
US8937660B2 (en) 2012-08-06 2015-01-20 Cloudparc, Inc. Profiling and tracking vehicles using cameras
US9208619B1 (en) 2012-08-06 2015-12-08 Cloudparc, Inc. Tracking the use of at least one destination location
US8982214B2 (en) 2012-08-06 2015-03-17 Cloudparc, Inc. Controlling use of parking spaces using cameras and smart sensors
US8982215B2 (en) 2012-08-06 2015-03-17 Cloudparc, Inc. Controlling use of parking spaces using cameras and smart sensors
US8982213B2 (en) 2012-08-06 2015-03-17 Cloudparc, Inc. Controlling use of parking spaces using cameras and smart sensors
US9036027B2 (en) 2012-08-06 2015-05-19 Cloudparc, Inc. Tracking the use of at least one destination location
US9064414B2 (en) 2012-08-06 2015-06-23 Cloudparc, Inc. Indicator for automated parking systems
US9330303B2 (en) 2012-08-06 2016-05-03 Cloudparc, Inc. Controlling use of parking spaces using a smart sensor network
US20140218532A1 (en) * 2012-08-06 2014-08-07 Cloudparc, Inc. Defining a Handoff Zone for Tracking a Vehicle Between Cameras
US20140257943A1 (en) * 2012-08-06 2014-09-11 Cloudparc, Inc. Tracking Speeding Violations and Controlling Use of Parking Spaces Using Cameras
US9171382B2 (en) * 2012-08-06 2015-10-27 Cloudparc, Inc. Tracking speeding violations and controlling use of parking spaces using cameras
US9064415B2 (en) 2012-08-06 2015-06-23 Cloudparc, Inc. Tracking traffic violations within an intersection and controlling use of parking spaces using cameras
US9858480B2 (en) 2012-08-06 2018-01-02 Cloudparc, Inc. Tracking a vehicle using an unmanned aerial vehicle
US9390319B2 (en) 2012-08-06 2016-07-12 Cloudparc, Inc. Defining destination locations and restricted locations within an image stream
US9489839B2 (en) 2012-08-06 2016-11-08 Cloudparc, Inc. Tracking a vehicle using an unmanned aerial vehicle
US9652666B2 (en) 2012-08-06 2017-05-16 Cloudparc, Inc. Human review of an image stream for a parking camera system
US10521665B2 (en) 2012-08-06 2019-12-31 Cloudparc, Inc. Tracking a vehicle using an unmanned aerial vehicle
US9607214B2 (en) 2012-08-06 2017-03-28 Cloudparc, Inc. Tracking at least one object
EP2923335B1 (en) 2012-11-22 2020-03-18 R-Biopharm AG Test strip and methods and apparatus for reading the same
US20140368443A1 (en) * 2013-06-14 2014-12-18 Agilent Technologies, Inc. System for Automating Laboratory Experiments
US9354070B2 (en) 2013-10-31 2016-05-31 Crown Equipment Corporation Systems, methods, and industrial vehicles for determining the visibility of features
US10401471B2 (en) 2014-02-06 2019-09-03 Fedex Corporate Services, Inc. Object tracking method and system
US11002823B2 (en) 2014-02-06 2021-05-11 FedEx Corporate Services, Inc Object tracking method and system
US9547079B2 (en) 2014-02-06 2017-01-17 Fedex Corporate Services, Inc. Object tracking method and system
US11747432B2 (en) 2014-02-06 2023-09-05 Fedex Corporate Servics, Inc. Object tracking method and system
US9886036B2 (en) 2014-02-10 2018-02-06 John Bean Technologies Corporation Routing of automated guided vehicles
US9599480B2 (en) 2015-03-06 2017-03-21 Umm Al-Qura University Vehicle localization and transmission method and system using a plurality of communication methods
US10466692B2 (en) 2015-03-10 2019-11-05 John Bean Technologies Corporation Automated guided vehicle system
US9864371B2 (en) 2015-03-10 2018-01-09 John Bean Technologies Corporation Automated guided vehicle system
US10803420B2 (en) 2016-09-30 2020-10-13 Staples, Inc. Hybrid modular storage fetching system
US11697554B2 (en) 2016-09-30 2023-07-11 Staples, Inc. Hybrid modular storage fetching system
US12037195B2 (en) 2016-09-30 2024-07-16 Staples, Inc. Hybrid modular storage fetching system
US11893535B2 (en) 2016-09-30 2024-02-06 Staples, Inc. Hybrid modular storage fetching system
US10683171B2 (en) 2016-09-30 2020-06-16 Staples, Inc. Hybrid modular storage fetching system
US11702287B2 (en) 2016-09-30 2023-07-18 Staples, Inc. Hybrid modular storage fetching system
US10589931B2 (en) 2016-09-30 2020-03-17 Staples, Inc. Hybrid modular storage fetching system
US20230092401A1 (en) * 2017-11-17 2023-03-23 Divine Logic, Inc. Systems and methods for tracking items
US10960939B1 (en) 2018-02-20 2021-03-30 Zoox, Inc. Worm gear drive unit interface and assembly methods
US10780930B1 (en) * 2018-02-20 2020-09-22 Zoox, Inc. Worm gear drive unit interface and assembly methods
US11084410B1 (en) 2018-08-07 2021-08-10 Staples, Inc. Automated guided vehicle for transporting shelving units
US11590997B1 (en) 2018-08-07 2023-02-28 Staples, Inc. Autonomous shopping cart
US11630447B1 (en) 2018-08-10 2023-04-18 Staples, Inc. Automated guided vehicle for transporting objects
US20210312661A1 (en) * 2018-12-28 2021-10-07 Panasonic Intellectual Property Management Co., Ltd. Positioning apparatus capable of measuring position of moving body using image capturing apparatus
US11180069B2 (en) 2018-12-31 2021-11-23 Staples, Inc. Automated loading of delivery vehicles using automated guided vehicles
US11119487B2 (en) 2018-12-31 2021-09-14 Staples, Inc. Automated preparation of deliveries in delivery vehicles using automated guided vehicles
US11124401B1 (en) 2019-03-31 2021-09-21 Staples, Inc. Automated loading of delivery vehicles
US11946771B2 (en) 2020-04-01 2024-04-02 Industrial Technology Research Institute Aerial vehicle and orientation detection method using same

Also Published As

Publication number Publication date
US20060184013A1 (en) 2006-08-17
US7845560B2 (en) 2010-12-07
WO2006065563A2 (en) 2006-06-22
EP1828862A2 (en) 2007-09-05
US20110121068A1 (en) 2011-05-26
WO2006065563A3 (en) 2007-04-19

Similar Documents

Publication Publication Date Title
US8196835B2 (en) Method and apparatus for determining position and rotational orientation of an object
US8381982B2 (en) Method and apparatus for managing and controlling manned and automated utility vehicles
US8210435B2 (en) Optical position marker apparatus
US11727349B2 (en) Automated warehousing using robotic forklifts or other material handling vehicles
US8807428B2 (en) Navigation of mobile devices
US8565913B2 (en) Apparatus and method for asset tracking
US11614743B2 (en) System and method for navigating a sensor-equipped mobile platform through an environment to a destination
CN101661098B (en) Multi-robot automatic locating system for robot restaurant
US20140267703A1 (en) Method and Apparatus of Mapping Landmark Position and Orientation
US9587948B2 (en) Method for determining the absolute position of a mobile unit, and mobile unit
US5051906A (en) Mobile robot navigation employing retroreflective ceiling features
CN111386529A (en) System and method for quickly identifying and processing image regions of interest
AU2023254997A1 (en) Recharging Control Method of Desktop Robot
US20070007354A1 (en) Remote crane bar code system
TW201925724A (en) Image processing device, mobile robot control system, and mobile robot control method
US8421674B2 (en) Localization system for determining a position of a device that can be moved on the floor
Mautz et al. Optical indoor positioning systems
Figat et al. NAO-mark vs QR-code Recognition by NAO Robot Vision
CN112074706A (en) Accurate positioning system
US20240127471A1 (en) Information processing apparatus, information processing system, information processing method, and recording medium
KR20090020027A (en) Apparatus and method for detecting a localization of mobility
Udvardy et al. Advanced navigation of automated vehicles in smart manufacturing
KR101955470B1 (en) Method and apparatus for indoor location tracking using rfid
WO2023062532A1 (en) Reference based positioning system
CN117570977A (en) Positioning method and positioning device for robot, robot and storage medium

Legal Events

Date Code Title Description
AS Assignment

Owner name: SKY-TRAX, INC., DELAWARE

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:EMANUEL, DAVID C.;MAHAN, LARRY G.;UNGERBUEHLER, RICHARD H.;SIGNING DATES FROM 20101209 TO 20101213;REEL/FRAME:025866/0581

STCF Information on status: patent grant

Free format text: PATENTED CASE

AS Assignment

Owner name: TOTALTRAX, INC., DELAWARE

Free format text: MERGER;ASSIGNOR:SKY-TRAX, LLC;REEL/FRAME:032948/0804

Effective date: 20140421

Owner name: SKY-TRAX, LLC, DELAWARE

Free format text: MERGER AND CHANGE OF NAME;ASSIGNORS:SKY-TRAX INCORPORATED;RTAC MERGER SUB, LLC;REEL/FRAME:032948/0681

Effective date: 20110708

AS Assignment

Owner name: ENHANCED CREDIT SUPPORTED LOAN FUND, LP, NEW YORK

Free format text: SECURITY INTEREST;ASSIGNOR:TOTALTRAX, INC;REEL/FRAME:033080/0298

Effective date: 20131204

FPAY Fee payment

Year of fee payment: 4

AS Assignment

Owner name: PINNACLE BANK, TENNESSEE

Free format text: SECURITY INTEREST;ASSIGNOR:TOTALTRAX, INC.;REEL/FRAME:040289/0708

Effective date: 20161110

MAFP Maintenance fee payment

Free format text: PAYMENT OF MAINTENANCE FEE, 8TH YR, SMALL ENTITY (ORIGINAL EVENT CODE: M2552); ENTITY STATUS OF PATENT OWNER: SMALL ENTITY

Year of fee payment: 8

AS Assignment

Owner name: TOTALTRAX INC., DELAWARE

Free format text: RELEASE BY SECURED PARTY;ASSIGNOR:ENHANCED CREDIT SUPPORTED LOAN FUND, LP;REEL/FRAME:059636/0751

Effective date: 20161115

Owner name: TOTALTRAX INC., DELAWARE

Free format text: RELEASE BY SECURED PARTY;ASSIGNOR:PINNACLE BANK;REEL/FRAME:059639/0221

Effective date: 20220419

AS Assignment

Owner name: TOTALTRAX INC., DELAWARE

Free format text: RELEASE BY SECURED PARTY;ASSIGNOR:PINNACLE BANK;REEL/FRAME:059651/0439

Effective date: 20220419

FEPP Fee payment procedure

Free format text: ENTITY STATUS SET TO UNDISCOUNTED (ORIGINAL EVENT CODE: BIG.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

AS Assignment

Owner name: SHENZHEN INVENTION DISCOVERY CO., LTD., CHINA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:INC., TOTALTRAX;REEL/FRAME:060212/0619

Effective date: 20220420

RR Request for reexamination filed

Effective date: 20220729

LIMR Reexamination decision: claims changed and/or cancelled

Kind code of ref document: C1

Free format text: REEXAMINATION CERTIFICATE; CLAIMS 3 AND 4 ARE CANCELLED. CLAIMS 1, 2 AND 5 ARE DETERMINED TO BE PATENTABLE AS AMENDED. CLAIMS 6-10, DEPENDENT ON AN AMENDED CLAIM, ARE DETERMINED TO BE PATENTABLE.

Filing date: 20220729

Effective date: 20230320

MAFP Maintenance fee payment

Free format text: PAYMENT OF MAINTENANCE FEE, 12TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1553); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

Year of fee payment: 12